1. The ORFEO Tool Box Software Guide
Updated for OTB-3.20
OTB Development Team
November 12, 2013
http://www.orfeo-toolbox.org
e-mail: otb@cnes.fr

3. The ORFEO Toolbox is not a black box.
Ch.D.

5. FOREWORD
Beside the Pleiades (PHR) and Cosmo-Skymed (CSK) systems developments forming ORFEO,
the dual and bilateral system (France - Italy) for Earth Observation, the ORFEO Accompaniment
Program was set up, to prepare, accompany and promote the use and the exploitation of the images
derived from these sensors.
The creation of a preparatory program1 is needed because of:
• the new capabilities and performances of the ORFEO systems (optical and radar high resolu-
tion, access capability, data quality, possibility to acquire simultaneously in optic and radar),
• the implied need of new methodological developments : new processing methods, or adapta-
tion of existing methods,
• the need to realise those new developments in very close cooperation with the final users for
better integration of new products in their systems.
This program was initiated by CNES mid-2003 and will last until mid 2013. It consists in two parts,
between which it is necessary to keep a strong interaction:
• A Thematic part,
• A Methodological part.
The Thematic part covers a large range of applications (civil and defence), and aims at specifying and
validating value added products and services required by end users. This part includes consideration
about products integration in the operational systems or processing chains. It also includes a careful
thought on intermediary structures to be developed to help non-autonomous users. Lastly, this part
aims at raising future users awareness, through practical demonstrations and validations.
1http://smsc.cnes.fr/PLEIADES/A prog accomp.htm

6. iv
The Methodological part objective is the definition and the development of tools for the operational
exploitation of the submetric optic and radar images (tridimensional aspects, changes detection,
texture analysis, pattern matching, optic radar complementarities). It is mainly based on R&D
studies and doctorate and post-doctorate researches.
In this context, CNES2 decided to develop the ORFEO ToolBox (OTB), a set of algorithms encapsu-
lated in a software library. The goals of the OTB is to capitalise a methological savoir faire in order
to adopt an incremental development approach aiming to efficiently exploit the results obtained in
the frame of methodological R&D studies.
All the developments are based on FLOSS (Free/Libre Open Source Software)
or existing CNES developments. OTB is distributed under the C´eCILL licence,
http://www.cecill.info/licences/Licence_CeCILL_V2-en.html.
OTB is implemented in C++ and is mainly based on ITK3 (Insight Toolkit).
2http://www.cnes.fr
3http://www.itk.org

7. CONTENTS
I Introduction 1
1 Welcome 3
1.1 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.2 How to Learn OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3
1.3 Software Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.3.1 Obtaining the Software . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4 Downloading OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
1.4.1 Join the Mailing List . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.2 Directory Structure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
1.4.3 Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7
1.4.4 Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.5 The OTB Community and Support . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6 A Brief History of OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8
1.6.1 ITK’s history . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10
2 Installation 11
2.1 Installing binary packages . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.1 Windows 2000/XP/Vista/Seven . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12
2.1.2 MacOS X . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
2.1.3 Linux . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

8. vi CONTENTS
Ubuntu 10.04 and higher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
OpenSuse 11.X and higher . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15
CentOS 5.5 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.2 Building from sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
2.2.1 Getting the OTB source code . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2.2 External Libraries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17
2.2.3 Configuring OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Preparing CMake . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18
Compiling OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
2.3 Getting Started With OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21
2.3.1 Hello World ! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22
3 System Overview 25
3.1 System Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
3.2 Essential System Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 26
3.2.1 Generic Programming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.2.2 Include Files and Class Definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . 27
3.2.3 Object Factories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.4 Smart Pointers and Memory Management . . . . . . . . . . . . . . . . . . . . . . . 28
3.2.5 Error Handling and Exceptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29
3.2.6 Event Handling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 30
3.2.7 Multi-Threading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.3 Numerics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
3.4 Data Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32
3.5 Data Processing Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 34
3.6 Spatial Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35
II Tutorials 37
4 Building Simple Applications with OTB 39
4.1 Hello world . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
4.2 Pipeline basics: read and write . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41

9. CONTENTS vii
4.3 Filtering pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43
4.4 Handling types: scaling output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44
4.5 Working with multispectral or color images . . . . . . . . . . . . . . . . . . . . . . . . . . . 46
4.6 Parsing command line arguments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49
4.7 Viewer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 54
4.8 Going from raw satellite images to useful products . . . . . . . . . . . . . . . . . . . . . . . 56
III User’s guide 61
5 Data Representation 63
5.1 Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
5.1.1 Creating an Image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
5.1.2 Reading an Image from a File . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65
5.1.3 Accessing Pixel Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66
5.1.4 Defining Origin and Spacing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67
5.1.5 Accessing Image Metadata . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 70
5.1.6 RGB Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73
5.1.7 Vector Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
5.1.8 Importing Image Data from a Buffer . . . . . . . . . . . . . . . . . . . . . . . . . . 76
5.1.9 Image Lists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 79
5.2 PointSet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.2.1 Creating a PointSet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80
5.2.2 Getting Access to Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82
5.2.3 Getting Access to Data in Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . 84
5.2.4 Vectors as Pixel Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 86
5.3 Mesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.3.1 Creating a Mesh . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89
5.3.2 Inserting Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91
5.3.3 Managing Data in Cells . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94
5.4 Path . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 96
5.4.1 Creating a PolyLineParametricPath . . . . . . . . . . . . . . . . . . . . . . . . . . . 96

10. viii CONTENTS
6 Reading and Writing Images 99
6.1 Basic Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 99
6.2 Pluggable Factories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101
6.3 IO Streaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.3.1 Implicit Streaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
6.3.2 Explicit Streaming . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105
6.4 Reading and Writing RGB Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 107
6.5 Reading, Casting and Writing Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108
6.6 Extracting Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109
6.7 Reading and Writing Vector Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 111
6.7.1 Reading and Writing Complex Images . . . . . . . . . . . . . . . . . . . . . . . . . 111
6.8 Reading and Writing Multiband Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 112
6.8.1 Extracting ROIs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 114
6.9 Reading Image Series . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117
6.10 Extended filename for reader and writer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
6.10.1 Syntax . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
6.10.2 Reader options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 119
6.10.3 Writer options . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120
7 Reading and Writing Auxilary Data 123
7.1 Reading DEM Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 123
7.2 Elevation management with OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
7.3 Lidar data Files . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127
7.4 Reading and Writing Shapefiles and KML . . . . . . . . . . . . . . . . . . . . . . . . . . . 130
7.5 Handling large vector data through OGR . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133
8 Basic Filtering 139
8.1 Thresholding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
8.1.1 Binary Thresholding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 139
8.1.2 General Thresholding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141
8.1.3 Threshold to Point Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 146
8.2 Mathematical operations on images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147

11. CONTENTS ix
8.3 Gradients . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
8.3.1 Gradient Magnitude . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150
8.3.2 Gradient Magnitude With Smoothing . . . . . . . . . . . . . . . . . . . . . . . . . 152
8.3.3 Derivative Without Smoothing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 154
8.4 Second Order Derivatives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
8.4.1 Laplacian Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
Laplacian Filter Recursive Gaussian . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
8.5 Edge Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
8.5.1 Canny Edge Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
8.5.2 Ratio of Means Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
8.6 Neighborhood Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
8.6.1 Mean Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
8.6.2 Median Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
8.6.3 Mathematical Morphology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 167
Binary Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
Grayscale Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 170
8.7 Smoothing Filters . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172
8.7.1 Blurring . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
Discrete Gaussian . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 173
8.7.2 Edge Preserving Smoothing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
Introduction to Anisotropic Diffusion . . . . . . . . . . . . . . . . . . . . . . . . . . 175
Gradient Anisotropic Diffusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 177
Mean Shift filtering and clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . . 178
8.7.3 Edge Preserving Speckle Reduction Filters . . . . . . . . . . . . . . . . . . . . . . 180
8.7.4 Edge preserving Markov Random Field . . . . . . . . . . . . . . . . . . . . . . . . 183
8.8 Distance Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
8.9 Rasterization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188
9 Image Registration 191
9.1 Registration Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
9.2 ”Hello World” Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
9.3 Features of the Registration Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 200

12. x CONTENTS
9.3.1 Direction of the Transform Mapping . . . . . . . . . . . . . . . . . . . . . . . . . . 200
9.3.2 Registration is done in physical space . . . . . . . . . . . . . . . . . . . . . . . . . 202
9.4 Multi-Modality Registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
9.4.1 Viola-Wells Mutual Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . 203
9.5 Centered Transforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
9.5.1 Rigid Registration in 2D . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
9.5.2 Centered Affine Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213
9.6 Transforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
9.6.1 Geometrical Representation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
9.6.2 Transform General Properties . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 222
9.6.3 Identity Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
9.6.4 Translation Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
9.6.5 Scale Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
9.6.6 Scale Logarithmic Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
9.6.7 Euler2DTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226
9.6.8 CenteredRigid2DTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
9.6.9 Similarity2DTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
9.6.10 QuaternionRigidTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
9.6.11 VersorTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
9.6.12 VersorRigid3DTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
9.6.13 Euler3DTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
9.6.14 Similarity3DTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
9.6.15 Rigid3DPerspectiveTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
9.6.16 AffineTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
9.6.17 BSplineDeformableTransform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237
9.6.18 KernelTransforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 238
9.7 Metrics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 239
9.7.1 Mean Squares Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
Exploring a Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 240
9.7.2 Normalized Correlation Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241
9.7.3 Mean Reciprocal Square Differences . . . . . . . . . . . . . . . . . . . . . . . . . . 241

13. CONTENTS xi
9.7.4 Mutual Information Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
Parzen Windowing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242
Viola and Wells Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
Mattes et al. Implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
9.7.5 Kullback-Leibler distance metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . 244
9.7.6 Normalized Mutual Information Metric . . . . . . . . . . . . . . . . . . . . . . . . 245
9.7.7 Mean Squares Histogram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245
9.7.8 Correlation Coefficient Histogram . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
9.7.9 Cardinality Match Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
9.7.10 Kappa Statistics Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246
9.7.11 Gradient Difference Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
9.8 Optimizers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
9.9 Landmark-based registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 249
10 Disparity Map Estimation 255
10.1 Disparity Maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 255
10.1.1 Geometric deformation modeling . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257
10.1.2 Similarity measures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 259
10.1.3 The correlation coefficient . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261
10.2 Regular grid disparity map estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 261
10.3 Irregular grid disparity map estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 263
10.4 Stereo reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 269
11 Orthorectification and Map Projection 277
11.1 Sensor Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
11.1.1 Types of Sensor Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 278
11.1.2 Using Sensor Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 279
11.1.3 Evaluating Sensor Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 286
11.1.4 Limits of the Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288
11.2 Map Projections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288
11.3 Orthorectification with OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 291
11.4 Vector data projection manipulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 293

14. xii CONTENTS
11.5 Geometries projection manipulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 294
11.6 Elevation management with OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 296
11.7 Vector data area extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 298
12 Radiometry 301
12.1 Radiometric Indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301
12.1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 301
12.1.2 NDVI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302
12.1.3 ARVI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
12.1.4 AVI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307
12.2 Atmospheric Corrections . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 309
13 Image Fusion 319
13.1 Simple Pan Sharpening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 319
13.2 Bayesian Data Fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 322
14 Feature Extraction 327
14.1 Textures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327
14.1.1 Haralick Descriptors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 327
14.1.2 PanTex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330
14.1.3 Structural Feature Set . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331
14.2 Interest Points . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
14.2.1 Harris detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 333
14.2.2 SIFT detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 336
14.2.3 SURF detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340
14.3 Alignments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344
14.4 Lines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346
14.4.1 Line Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346
14.4.2 Segment Extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352
Local Hough Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 352
Line Segment Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354
14.4.3 Right Angle Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356
14.5 Density Features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358

15. CONTENTS xiii
14.5.1 Edge Density . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 359
14.5.2 SIFT Density . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360
14.6 Geometric Moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362
14.6.1 Complex Moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362
Complex Moments for Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362
Complex Moments for Paths . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 363
14.6.2 Hu Moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 364
Hu Moments for Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 365
14.6.3 Flusser Moments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
Flusser Moments for Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 366
14.7 Road extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 367
14.7.1 Road extraction filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 368
14.7.2 Step by step road extraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
14.8 Cloud Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 377
15 Multi-scale Analysis 381
15.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381
15.2 Morphological Pyramid . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 381
15.2.1 Morphological Pyramid Exploitation . . . . . . . . . . . . . . . . . . . . . . . . . . 388
16 Image Segmentation 395
16.1 Region Growing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 395
16.1.1 Connected Threshold . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 396
16.1.2 Otsu Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 399
16.1.3 Neighborhood Connected . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 403
16.1.4 Confidence Connected . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 406
16.2 Segmentation Based on Watersheds . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
16.2.1 Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
16.2.2 Using the ITK Watershed Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 412
16.3 Level Set Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
16.3.1 Fast Marching Segmentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 417
17 Image Simulation 425

16. xiv CONTENTS
17.1 PROSAIL model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 425
17.2 Image Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429
17.2.1 LAI image estimation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 429
17.2.2 Sensor RSR Image Simulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 431
18 Dimension Reduction 443
18.1 Principal Component Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 443
18.2 Noise-Adjusted Principal Components Analysis . . . . . . . . . . . . . . . . . . . . . . . . 445
18.3 Maximum Noise Fraction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 447
18.4 Fast Independant Component Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 450
18.5 Maximum Autocorrelation Factor . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 452
19 Classification 455
19.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455
19.2 Unsupervised classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455
19.2.1 K-Means Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455
Simple version . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 455
General approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 459
k-d Tree Based k-Means Clustering . . . . . . . . . . . . . . . . . . . . . . . . . . . 461
19.2.2 Kohonen’s Self Organizing Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466
Building a color table . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 467
SOM Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471
Multi-band, streamed classification . . . . . . . . . . . . . . . . . . . . . . . . . . . 474
19.2.3 Bayesian Plug-In Classifier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 475
19.2.4 Expectation Maximization Mixture Model Estimation . . . . . . . . . . . . . . . . . 480
19.2.5 Statistical Segmentations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 484
Stochastic Expectation Maximization . . . . . . . . . . . . . . . . . . . . . . . . . . 484
19.2.6 Classification using Markov Random Fields . . . . . . . . . . . . . . . . . . . . . . 487
ITK framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 487
OTB framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 492
19.3 Supervised classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501
19.3.1 Generic machine learning framework . . . . . . . . . . . . . . . . . . . . . . . . . 501

17. CONTENTS xv
19.3.2 An example of supervised classification method: Support Vector Machines . . . . . 502
SVM general description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502
SVM mathematical formulation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 502
19.3.3 Learning from samples . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 504
19.3.4 Learning from images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 506
19.3.5 Multi-band, streamed classification . . . . . . . . . . . . . . . . . . . . . . . . . . . 508
19.3.6 Generic Kernel SVM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 509
Learning with User Defined Kernels . . . . . . . . . . . . . . . . . . . . . . . . . . . 510
Classification with user defined kernel . . . . . . . . . . . . . . . . . . . . . . . . . . 512
19.4 Fusion of Classification maps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513
19.4.1 General approach of image fusion . . . . . . . . . . . . . . . . . . . . . . . . . . . 513
19.4.2 Majority voting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513
General description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 513
An example of majority voting fusion . . . . . . . . . . . . . . . . . . . . . . . . . . 513
19.4.3 Dempster Shafer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514
General description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 514
Mathematical formulation of the combination algorithm . . . . . . . . . . . . . . . . 515
An example of Dempster Shafer fusion . . . . . . . . . . . . . . . . . . . . . . . . . 515
19.5 Classification map regularization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 517
20 Object-based Image Analysis 521
20.1 From Images to Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 522
20.2 Object Attributes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523
20.3 Object Filtering based on radiometric and statistics attributes . . . . . . . . . . . . . . . . . . 525
20.4 Hoover metrics to compare segmentations . . . . . . . . . . . . . . . . . . . . . . . . . . . . 528
21 Change Detection 531
21.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 531
21.1.1 Surface-based approaches . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 532
21.2 Change Detection Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 533
21.3 Simple Detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 536
21.3.1 Mean Difference . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 536

18. xvi CONTENTS
21.3.2 Ratio Of Means . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 539
21.4 Statistical Detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 542
21.4.1 Distance between local distributions . . . . . . . . . . . . . . . . . . . . . . . . . . 542
21.4.2 Local Correlation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 544
21.5 Multi-Scale Detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547
21.5.1 Kullback-Leibler Distance between distributions . . . . . . . . . . . . . . . . . . . 547
21.6 Multi-components detectors . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549
21.6.1 Multivariate Alteration Detector . . . . . . . . . . . . . . . . . . . . . . . . . . . . 549
22 Geospatial analysis 553
22.1 Reading from and Writing to Geospatial DBs . . . . . . . . . . . . . . . . . . . . . . . . . . 553
23 Hyperspectral 555
23.1 Unmixing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556
23.1.1 Linear mixing model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556
23.1.2 Simplex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558
23.1.3 State of the art unmixing algorithms selection . . . . . . . . . . . . . . . . . . . . . 559
Family 1 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559
Family 2 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 559
Family 3 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561
Further remarks . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 561
Basic hyperspectral unmixing example . . . . . . . . . . . . . . . . . . . . . . . . . 562
23.2 Dimensionality reduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 563
23.3 Anomaly detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564
24 Image Visualization and output 569
24.1 Viewer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 569
24.2 Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 570
24.2.1 Grey Level Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 570
24.2.2 Multiband Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 572
24.2.3 Indexed Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 573
24.2.4 Altitude Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 574

19. CONTENTS xvii
25 Online data 579
25.1 Name to Coordinates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 579
25.2 Open Street Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 580
IV Developer’s guide 585
26 Iterators 587
26.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 587
26.2 Programming Interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 588
26.2.1 Creating Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 588
26.2.2 Moving Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 588
26.2.3 Accessing Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 590
26.2.4 Iteration Loops . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 591
26.3 Image Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 592
26.3.1 ImageRegionIterator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 592
26.3.2 ImageRegionIteratorWithIndex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 594
26.3.3 ImageLinearIteratorWithIndex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596
26.4 Neighborhood Iterators . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 598
26.4.1 NeighborhoodIterator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 604
Basic neighborhood techniques: edge detection . . . . . . . . . . . . . . . . . . . . . 604
Convolution filtering: Sobel operator . . . . . . . . . . . . . . . . . . . . . . . . . . 607
Optimizing iteration speed . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 608
Separable convolution: Gaussian filtering . . . . . . . . . . . . . . . . . . . . . . . . 610
Random access iteration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 611
26.4.2 ShapedNeighborhoodIterator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 613
Shaped neighborhoods: morphological operations . . . . . . . . . . . . . . . . . . . . 615
27 Image Adaptors 619
27.1 Image Casting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 620
27.2 Adapting RGB Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 622
27.3 Adapting Vector Images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 624
27.4 Adaptors for Simple Computation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 626

20. xviii CONTENTS
27.5 Adaptors and Writers . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 628
28 Streaming and Threading 629
28.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629
28.2 Streaming and threading in OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 629
28.3 Division strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 630
29 How To Write A Filter 631
29.1 Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 631
29.2 Overview of Filter Creation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 632
29.3 Streaming Large Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 633
29.3.1 Overview of Pipeline Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . 634
29.3.2 Details of Pipeline Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 636
UpdateOutputInformation() . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 636
PropagateRequestedRegion() . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 637
UpdateOutputData() . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 638
29.4 Threaded Filter Execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 638
29.5 Filter Conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 639
29.5.1 Optional . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 640
29.5.2 Useful Macros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 640
29.6 How To Write A Composite Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641
29.6.1 Implementing a Composite Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641
29.6.2 A Simple Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 642
30 Persistent filters 647
30.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 647
30.2 Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 647
30.2.1 The persistent filter class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 648
30.2.2 The streaming decorator class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 648
30.3 An end-to-end example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 649
30.3.1 First step: writing a persistent filter . . . . . . . . . . . . . . . . . . . . . . . . . . . 649
30.3.2 Second step: Decorating the filter and using it . . . . . . . . . . . . . . . . . . . . . 651
30.3.3 Third step: one class to rule them all . . . . . . . . . . . . . . . . . . . . . . . . . . 651

21. CONTENTS xix
31 How to write an application 653
31.1 Application design . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 653
31.2 Architecture of the class . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 654
31.2.1 DoInit() . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 654
31.2.2 DoUpdateParameters() . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 654
31.2.3 DoExecute() . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 654
31.2.4 Parameters selection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 655
31.2.5 Parameters description . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 656
31.3 Compile your application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 656
31.4 Execute your application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 657
31.5 Testing your application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 657
31.6 Application Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 657
V Appendix 661
32 Frequently Asked Questions 663
32.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663
32.1.1 What is OTB? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 663
32.1.2 What is ORFEO? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 664
Where can I get more information about ORFEO? . . . . . . . . . . . . . . . . . . . 664
32.1.3 What is the ORFEO Accompaniment Program? . . . . . . . . . . . . . . . . . . . . 664
Where can I get more information about the ORFEO Accompaniment Program? . . . 665
32.1.4 Who is responsible for the OTB development? . . . . . . . . . . . . . . . . . . . . . 665
32.2 Licence . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665
32.2.1 Which is the OTB licence? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 665
32.2.2 If I write an application using OTB am I forced to distribute that application? . . . . 666
32.2.3 If I write an application using OTB am I forced to contribute the code into the offical repositories?666
32.2.4 If I wanted to distribute an application using OTB what license would I need to use? 666
32.2.5 I am a commercial user. Is there any restriction on the use of OTB? . . . . . . . . . . 666
32.3 Getting OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 666
32.3.1 Who can download the OTB? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 666
32.3.2 Where can I download the OTB? . . . . . . . . . . . . . . . . . . . . . . . . . . . . 666

22. xx CONTENTS
32.3.3 How to get the latest bleeding-edge version? . . . . . . . . . . . . . . . . . . . . . . 667
32.4 Compiling and installing OTB from source . . . . . . . . . . . . . . . . . . . . . . . . . . . 667
32.4.1 Which platforms are supported? . . . . . . . . . . . . . . . . . . . . . . . . . . . . 667
32.4.2 Which libraries/packages are needed before compiling and installing OTB? . . . . . 667
32.4.3 Main steps . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 669
Unix/Linux Platforms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 669
Microsoft Visual Studio (Express 2008/Express 2010) . . . . . . . . . . . . . . . . . 671
32.4.4 Specific platform issues . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671
Visual Studio 2010/Express 2010 . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671
MacOSX 10.6 Snow Leopard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671
Debian Linux / Ubuntu . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 671
32.5 Using OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 672
32.5.1 Where to start ? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 672
32.5.2 What is the image size limitation of OTB ? . . . . . . . . . . . . . . . . . . . . . . 672
32.6 Getting help . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673
32.6.1 Is there any mailing list? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673
32.6.2 Which is the main source of documentation? . . . . . . . . . . . . . . . . . . . . . . 673
32.7 Contributing to OTB . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 673
32.7.1 I want to contribute to OTB, where to begin? . . . . . . . . . . . . . . . . . . . . . 673
32.7.2 What are the benefits of contributing to OTB? . . . . . . . . . . . . . . . . . . . . . 674
32.7.3 What functionality can I contribute? . . . . . . . . . . . . . . . . . . . . . . . . . . 674
32.8 Running the tests . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 674
32.8.1 What are the tests? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 674
32.8.2 How to run the tests? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675
32.8.3 How to get the test data? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 675
32.8.4 How to submit the results? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 676
32.9 OTB’s Roadmap . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 676
32.9.1 Which will be the next version of OTB? . . . . . . . . . . . . . . . . . . . . . . . . 676
What is a major version? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 676
What is a minor version? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 676
What is a bugfix version? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 677

23. CONTENTS xxi
32.9.2 When will the next version of OTB be available? . . . . . . . . . . . . . . . . . . . 677
32.9.3 What features will the OTB include and when? . . . . . . . . . . . . . . . . . . . . 677
33 Release Notes 679
34 Wrappings to other languages 733
34.1 OTB-Wrapping: bindings to Java language . . . . . . . . . . . . . . . . . . . . . . . . . . . 733
34.1.1 Mangling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 733
34.1.2 How to Use OTB-Wrapping in Java . . . . . . . . . . . . . . . . . . . . . . . . . . 734
Import OTB classes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 734
Compile Java programs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 734
Java programs execution . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 735
34.1.3 Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 736
34.1.4 Use OTB-Wrapping . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 737
Download sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 737
Required Tools . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 737
Compile OTB-Wrapping sources . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 737
Download binaries . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 738
Use OTB-Wrapping with Eclipse . . . . . . . . . . . . . . . . . . . . . . . . . . . . 738
34.2 Java tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 738
34.2.1 Hello World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 738
34.2.2 Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 739
34.2.3 Filtering pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 739
34.2.4 Smarter Filtering Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 740
34.2.5 Scaling Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 742
34.2.6 MultiSpectral . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 743
34.2.7 OrthoFusion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 745
34.3 Python tutorials . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 748
34.3.1 Hello World . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 748
34.3.2 Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 749
34.3.3 Filtering pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 749
34.3.4 Smarter Filtering Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 750

24. xxii CONTENTS
34.3.5 Scaling Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 752
34.3.6 MultiSpectral . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 753
34.4 Developer Guide . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 756
34.4.1 Add a new Library : Creating a new CMakeList.txt file . . . . . . . . . . . . . . . . 756
34.4.2 Add a new cmake file . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 756
A simple Example : otb::StreamingShrinkImageFilter . . . . . . . . . . . . . . . . . 757
34.4.3 Predefined Macros . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 757
OTB-Wrapping predefined variables . . . . . . . . . . . . . . . . . . . . . . . . . . . 758
OTB-Wrapping predefined lists . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 758
Macro MANGLE NAME . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 760
34.4.4 HTML JavaDoc generation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 760
Generate JavaDoc documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . . 760
Generate JavaDoc while compilation . . . . . . . . . . . . . . . . . . . . . . . . . . 761
35 Contributors 763
Index 777

25. LIST OF FIGURES
2.1 Cmake user interface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
5.1 OTB Image Geometrical Concepts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 68
5.2 PointSet with Vectors as PixelType . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87
6.1 Collaboration diagram of the ImageIO classes . . . . . . . . . . . . . . . . . . . . . . . . . . 101
6.2 Use cases of ImageIO factories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
6.3 Class diagram of ImageIO factories . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102
6.4 Initial SPOT 5 image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
6.5 ROI of a SPOT5 image . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 116
7.1 DEM To Image generator Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 125
7.2 Image from lidar data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 131
8.1 BinaryThresholdImageFilter transfer function . . . . . . . . . . . . . . . . . . . . . . . . . . 140
8.2 BinaryThresholdImageFilter output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 142
8.3 ThresholdImageFilter using the threshold-below mode. . . . . . . . . . . . . . . . . . . . . . 142
8.4 ThresholdImageFilter using the threshold-above mode . . . . . . . . . . . . . . . . . . . . . 143
8.5 ThresholdImageFilter using the threshold-outside mode . . . . . . . . . . . . . . . . . . . . . 143
8.6 Band Math . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149
8.7 GradientMagnitudeImageFilter output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 151

26. xxiv List of Figures
8.8 GradientMagnitudeRecursiveGaussianImageFilter output . . . . . . . . . . . . . . . . . . . . 153
8.9 Effect of the Derivative filter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155
8.10 Output of the RecursiveGaussianImageFilter. . . . . . . . . . . . . . . . . . . . . . . . . . . 159
8.11 Output of the LaplacianRecursiveGaussianImageFilter. . . . . . . . . . . . . . . . . . . . . . 160
8.12 CannyEdgeDetectorImageFilter output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161
8.13 Touzi Edge Detector Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164
8.14 Effect of the MedianImageFilter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
8.15 Effect of the Median filter. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 168
8.16 Effect of erosion and dilation in a binary image. . . . . . . . . . . . . . . . . . . . . . . . . . 170
8.17 Effect of erosion and dilation in a grayscale image. . . . . . . . . . . . . . . . . . . . . . . . 172
8.18 DiscreteGaussianImageFilter Gaussian diagram. . . . . . . . . . . . . . . . . . . . . . . . . . 173
8.19 DiscreteGaussianImageFilter output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175
8.20 GradientAnisotropicDiffusionImageFilter output . . . . . . . . . . . . . . . . . . . . . . . . 178
8.21 Mean Shift . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 180
8.22 Lee Filter Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 182
8.23 Frost Filter Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 183
8.24 MRF restauration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 186
8.25 DanielssonDistanceMapImageFilter output . . . . . . . . . . . . . . . . . . . . . . . . . . . 187
8.26 Rasterized SRTM water bodies near Arcachon, France. . . . . . . . . . . . . . . . . . . . . . 190
9.1 Image Registration Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 191
9.2 Registration Framework Components . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 192
9.3 Fixed and Moving images in registration framework . . . . . . . . . . . . . . . . . . . . . . . 197
9.4 HelloWorld registration output images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 198
9.5 Pipeline structure of the registration example . . . . . . . . . . . . . . . . . . . . . . . . . . 199
9.6 Registration Coordinate Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 201
9.7 Multi-Modality Registration Inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 207
9.8 Multi-Modality Registration outputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 208
9.9 Rigid2D Registration input images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
9.10 Rigid2D Registration output images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 212
9.11 Rigid2D Registration input images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214
9.12 Rigid2D Registration output images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214

27. List of Figures xxv
9.13 AffineTransform registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 218
9.14 AffineTransform output images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
9.15 Geometrical representation objects in ITK . . . . . . . . . . . . . . . . . . . . . . . . . . . . 219
9.16 Parzen Windowing in Mutual Information . . . . . . . . . . . . . . . . . . . . . . . . . . . . 243
9.17 Class diagram of the Optimizer hierarchy . . . . . . . . . . . . . . . . . . . . . . . . . . . . 247
9.18 Estimation of affine transformation using least square optimisation from SIFT points . . . . . 253
10.1 Estimation of the correlation surface. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 260
10.2 Deformation field and resampling from fine registration . . . . . . . . . . . . . . . . . . . . . 263
10.3 Deformation field and resampling from disparity map estimation . . . . . . . . . . . . . . . . 270
10.4 From stereo pair to elevation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 276
11.1 Image Ortho-registration Procedure . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 277
12.1 ARVI Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 305
12.2 ARVI Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 307
12.3 AVI Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 310
13.1 Simple pan-sharpening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 320
13.2 Pan sharpening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 321
13.3 Bayesian Data Fusion Example inputs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 324
13.4 Bayesian Data Fusion results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 325
14.1 Results of applying Haralick contrast . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 330
14.2 PanTex Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 331
14.3 Right Angle Detection Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 334
14.4 Harris Filter Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 335
14.5 SIFT Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 340
14.6 SURF Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 344
14.7 Alignment Detection Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 346
14.8 Line Ratio Detector Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 348
14.9 Line Correlation Detector Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 351
14.10Line Correlation Detector Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 353

28. xxvi List of Figures
14.11Line Correlation Detector Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 354
14.12LSD Application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 356
14.13Right Angle Detection Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 358
14.14Edge Density Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 360
14.15SIFT Density Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 362
14.16Road extraction filter application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 371
14.17Spectral Angle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 372
14.18Road extraction filter application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376
14.19Road extraction filter application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 376
14.20Cloud Detection Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 379
15.1 Morphological pyramid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385
15.2 Morphological pyramid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385
15.3 Morphological pyramid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385
15.4 Morphological pyramid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 385
15.5 Morphological pyramid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386
15.6 Morphological pyramid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386
15.7 Morphological pyramid analysis and synthesis . . . . . . . . . . . . . . . . . . . . . . . . . . 389
15.8 Morphological pyramid analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 391
16.1 ConnectedThreshold segmentation results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398
16.2 OtsuThresholdImageFilter output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 400
16.3 OtsuThresholdImageFilter output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 402
16.4 NeighborhoodConnectedThreshold segmentation results . . . . . . . . . . . . . . . . . . . . 405
16.5 ConfidenceConnected segmentation results . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
16.6 Watershed Catchment Basins . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 410
16.7 Watersheds Hierarchy of Regions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411
16.8 Watersheds filter composition . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 411
16.9 Watershed segmentation output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 414
16.10Zero Set Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415
16.11Grid position of the embedded level-set surface. . . . . . . . . . . . . . . . . . . . . . . . . . 416
16.12FastMarchingImageFilter collaboration diagram . . . . . . . . . . . . . . . . . . . . . . . . . 417

29. List of Figures xxvii
16.13FastMarchingImageFilter intermediate output . . . . . . . . . . . . . . . . . . . . . . . . . . 423
16.14FastMarchingImageFilter segmentations . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 424
17.1 LAIFromNDVIImageTransform Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 430
18.1 PCA Filter (forward trasnformation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 445
18.2 PCA Filter (forward trasnformation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 448
18.3 PCA Filter (forward trasnformation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 450
18.4 PCA Filter (forward trasnformation) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 453
18.5 Maximum Autocorrelation Factor results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 454
19.1 Output of the KMeans classifier . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 458
19.2 Two normal distributions plot . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 463
19.3 Kohonen’s Self Organizing Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 466
19.4 SOM Image Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471
19.5 SOM Image Classification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 474
19.6 Bayesian plug-in classifier for two Gaussian classes . . . . . . . . . . . . . . . . . . . . . . . 476
19.7 SEM Classification results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 487
19.8 Output of the ScalarImageMarkovRandomField . . . . . . . . . . . . . . . . . . . . . . . . . 492
19.9 OTB Markov Framework . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 493
19.10MRF restauration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 496
19.11MRF restauration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 497
19.12MRF restauration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 500
19.13MRF restauration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 501
20.1 Image to Label Object Map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 523
20.2 Object based extraction based on . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 527
21.1 Spot Images for Change Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 537
21.2 Difference Change Detection Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 539
21.3 Radarsat Images for Change Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 540
21.4 Ratio Change Detection Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 541
21.5 Kullback-Leibler Change Detection Results . . . . . . . . . . . . . . . . . . . . . . . . . . . 544

30. xxviii List of Figures
21.6 ERS Images for Change Detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 545
21.7 Correlation Change Detection Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 547
21.8 Kullback-Leibler profile Change Detection Results . . . . . . . . . . . . . . . . . . . . . . . 549
21.9 Multivariate Alteration Detection Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . 551
23.1 Hyperspectral cube . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 555
23.2 Linear mixing model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556
23.3 Decomposition of the LMM . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 556
23.4 Hyperspectral cube vectorization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 557
23.5 Simplex . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 558
23.6 Unmixing Filter . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 564
23.7 Concept of detection . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 565
23.8 Anomaly detection block diagram . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 566
23.9 Sliding window and parameters definitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . 567
24.1 Image visualization. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 571
24.2 Scaling images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 572
24.3 Scaling images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 574
24.4 Scaling images . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 575
24.5 Grayscale to color . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 576
24.6 Hill shading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 577
25.1 Open street map . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 583
26.1 ITK image iteration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 589
26.2 Copying an image subregion using ImageRegionIterator . . . . . . . . . . . . . . . . . . . . 595
26.3 Using the ImageRegionIteratorWithIndex . . . . . . . . . . . . . . . . . . . . . . . . . . . . 596
26.4 Neighborhood iterator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599
26.5 Some possible neighborhood iterator shapes . . . . . . . . . . . . . . . . . . . . . . . . . . . 600
26.6 Sobel edge detection results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 607
26.7 Gaussian blurring by convolution filtering . . . . . . . . . . . . . . . . . . . . . . . . . . . . 612
26.8 Finding local minima . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 613
26.9 Binary image morphology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 618

31. List of Figures xxix
27.1 ImageAdaptor concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 620
27.2 Image Adaptor for performing computations . . . . . . . . . . . . . . . . . . . . . . . . . . . 627
29.1 Relationship between DataObjects and ProcessObjects . . . . . . . . . . . . . . . . . . . . . 632
29.2 The Data Pipeline . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 634
29.3 Sequence of the Data Pipeline updating mechanism . . . . . . . . . . . . . . . . . . . . . . . 635
29.4 Composite Filter Concept . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 641
29.5 Composite Filter Example . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 642

33. LIST OF TABLES
2.1 Available installation procedures with respect to system configuration and target usage . . . . 12
9.1 Geometrical Elementary Objects . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220
9.2 Identity Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 223
9.3 Translation Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 224
9.4 Scale Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225
9.5 Scale Logarithmic Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 226
9.6 Euler2D Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 227
9.7 CenteredRigid2D Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . 228
9.8 Similarity2D Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229
9.9 QuaternionRigid Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . 230
9.10 Versor Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 231
9.11 Versor Rigid3D Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . 232
9.12 Euler3D Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233
9.13 Similarity3D Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234
9.14 Rigid3DPerspective Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . 235
9.15 Affine Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 236
9.16 BSpline Deformable Transform Characteristics . . . . . . . . . . . . . . . . . . . . . . . . . 237
10.1 Characterization of the geometric deformation sources . . . . . . . . . . . . . . . . . . . . . 257
10.2 Approaches to image registration . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 258

34. xxxii List of Tables
12.1 Vegetation indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302
12.2 Soil indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 302
12.3 Water indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303
12.4 Built-up indices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 303
14.1 Haralick features . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 328
16.1 ConnectedThreshold example parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 398
16.2 NeighborhoodConnectedThreshold example parameters . . . . . . . . . . . . . . . . . . . . . 405
16.3 ConnectedThreshold example parameters . . . . . . . . . . . . . . . . . . . . . . . . . . . . 409
16.4 FastMarching segmentation example parameters . . . . . . . . . . . . . . . . . . . . . . . . . 422
32.1 Libraries used in the OTB. In the column Where, the default behavior during the configuration of OTB is indicated by when the
34.1 Mangling of the basic types used. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 734
34.2 Mangling of the usually types used. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 734
34.3 C++ code translation. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 736

35. Part I
Introduction

37. CHAPTER
ONE
WELCOME
Welcome to the ORFEO ToolBox (OTB) Software Guide.
This document presents the essential concepts used in OTB. It will guide you through the road
of learning and using OTB. The Doxygen documentation for the OTB application programming
interface is available on line at http://orfeo-toolbox.sourceforge.net/Doxygen/html.
1.1 Organization
This software guide is divided into several parts, each of which is further divided into several chap-
ters. Part I is a general introduction to OTB, with—in the next chapter—a description of how to
install the ORFEO Toolbox on your computer. Part I also introduces basic system concepts such
as an overview of the system architecture, and how to build applications in the C++ programming
language. Part II is a short guide with gradual difficulty to get you start programming with OTB.
Part III describes the system from the user point of view. Dozens of examples are used to illustrate
important system features. Part IV is for the OTB developer. It explains how to create your own
classes and extend the system.
1.2 How to Learn OTB
There are two broad categories of users of OTB. First are class developers, those who create classes
in C++. The second, users, employ existing C++ classes to build applications. Class developers
must be proficient in C++, and if they are extending or modifying OTB, they must also be familiar
with OTB’s internal structures and design (material covered in Part IV).
The key to learning how to use OTB is to become familiar with its palette of objects and the ways
of combining them. We recommend that you learn the system by studying the examples and then,
if you are a class developer, study the source code. Start by the first few tutorials in Part II to get

38. 4 Chapter 1. Welcome
familiar with the build process and the general program organization, follow by reading Chapter 3,
which provides an overview of some of the key concepts in the system, and then review the exam-
ples in Part III. You may also wish to compile and run the dozens of examples distributed with the
source code found in the directory OTB/Examples. (Please see the file OTB/Examples/README.txt
for a description of the examples contained in the various subdirectories.) There are also several
hundreds of tests found in the source distribution in OTB/Testing/Code, most of which are mini-
mally documented testing code. However, they may be useful to see how classes are used together
in OTB, especially since they are designed to exercise as much of the functionality of each class as
possible.
1.3 Software Organization
The following sections describe the directory contents, summarize the software functionality in each
directory, and locate the documentation and data.
1.3.1 Obtaining the Software
Periodic releases of the software are available on the OTB Web site. These official releases are
available a few times a year and announced on the ORFEO Web pages and mailing lists.
This software guide assumes that you are working with the latest official OTB release (available on
the OTB Web site).
1.4 Downloading OTB
OTB can be downloaded without cost from the following web site:
http://www.orfeo-toolbox.org/
In order to track the kind of applications for which OTB is being used, you will be asked to complete
a form prior to downloading the software. The information you provide in this form will help
developers to get a better idea of the interests and skills of the toolkit users.
Once you fill out this form you will have access to the download page. This page can be book
marked to facilitate subsequent visits to the download site without having to complete any form
again.
Then choose the tarball that better fits your system. The options are .zip and .tgz files. The
first type is better suited for MS-Windows while the second one is the preferred format for UNIX
systems.

39. 1.4. Downloading OTB 5
Once you unzip or untar the file, a directory called OTB will be created in your disk and you will be
ready for starting the configuration process described in Section 2.2.3 on page 18.
You can also get the current version following instructions in Section 32.3.3, on page 667.
1.4.1 Join the Mailing List
It is strongly recommended that you join the users mailing list. This is one of the primary resources
for guidance and help regarding the use of the toolkit. You can subscribe to the users list online at
http://groups.google.com/group/otb-users
The otb-users mailing list is also the best mechanism for expressing your opinions about the toolbox
and to let developers know about features that you find useful, desirable or even unnecessary. OTB
developers are committed to creating a self-sustaining open-source OTB community. Feedback from
users is fundamental to achieving this goal.
1.4.2 Directory Structure
To begin your OTB odyssey, you will first need to know something about OTB’s software organiza-
tion and directory structure. It is helpful to know enough to navigate through the code base to find
examples, code, and documentation.
OTB is organized into several different modules. There are three: the OTB, OTB-Documents and
OTB-Wrapping modules. The source code, examples and applications are found in the OTB module;
documentation, tutorials, and material related to the design and marketing of OTB are found in
OTB-Documents; and resources to wrap OTB classes into other languages (such as Java or Python)
are available from OTB-Wrapping. Usually you will work with the OTB module unless you are a
developer, are teaching a course, or are looking at the details of various design documents.
The OTB module contains the following subdirectories:
• OTB/Code—the heart of the software; the location of the majority of the source code.
• OTB/Applications—a set of applications modules that can be launched in different ways
(command-line, graphical interface, Python/Java), refer to the OTB Cookbook for more infor-
mation
• OTB/CMake—internal files used during the configuration process
• OTB/Copyright—the copyright information of OTB and all the dependencies included in the
OTB source tree
• OTB/Examples—a suite of simple, well-documented examples used by this guide and to il-
lustrate important OTB concepts.

40. 6 Chapter 1. Welcome
• OTB/Testing—a large number of small programs used to test OTB. These examples tend to
be minimally documented but may be useful to demonstrate various system concepts.
• OTB/Utilities—supporting software for the OTB source code. For example, libraries such
as ITK.GDAL.
The source code directory structure—found in OTB/Code—is important to understand since other
directory structures (such as the Testing directory) shadow the structure of the OTB/Code directory.
• OTB/Code/ApplicationEngine—the core library for building applications based on OTB
• OTB/Code/Common—core classes, macro definitions, typedefs, and other software constructs
central to OTB.
• OTB/Code/BasicFilters—basic image processing filters.
• OTB/Code/Fusion—image fusion algorithms, as for instance, pansharpening.
• OTB/Code/FeatureExtraction—the location of many feature extraction algorithms.
• OTB/Code/ChangeDetection—a set of remote sensing image change detection algorithms.
• OTB/Code/DisparityMap—tools for estimating disparities – deformations – between im-
ages.
• OTB/Code/Fuzzy—fuzzy logic based algorithms, with Dempster-Shaffer theory related
classes
• OTB/Code/GeospatialAnalysis—classes allowing to connect to geospatial database like
PostGIS.
• OTB/Code/Gui—very basic widgets for building graphical user interfaces, such as progress
bars for filters, etc.
• OTB/Code/Hyperspectral—hyperspectral images analysis
• OTB/Code/IO—classes that support the reading and writing of data.
• OTB/Code/Learning—several functionnalities for supervised learning and classification.
• OTB/Code/Markov—implementation of Markov Random Fields regularization and segmen-
tation.
• OTB/Code/MultiScale—a set of functionalities for multiscale image analysis and synthesis.
• OTB/Code/MultiTemporal—time series interpolation related algorithms
• OTB/Code/OBIA—Object Based Image Analysis filters and data structures
• OTB/Code/ObjectDetection—Object detection chain based on local feature extraction

41. 1.4. Downloading OTB 7
• OTB/Code/Projections—classes allowing to deal with sensor models and cartographic pro-
jections.
• OTB/Code/Radiometry—classes allowing to compute vegetation indices and radiometric
corrections.
• OTB/Code/SARPolarimetry—some add-ons for SAR polarimetry synthesis and analysis.
• OTB/Code/Segmentation—several functionnalities for image segmentation.
• OTB/Code/Simulation—Sensor simulator
• OTB/Code/SpatialReasoning—several functionnalities high level image analysis using
spatial reasoning techniques.
• OTB/Code/Testing—internal classes used in the used in the testing framework
• OTB/Code/Visualization—utilities for simple image visualization.
• OTB/Code/Wrappers—wrappers of applications in several access points (command-line, QT
Gui, SWIG...).
The OTB-Documents module contains the following subdirectories:
• OTB-Documents/CourseWare—material related to teaching OTB.
• OTB-Documents/Latex—LATEX styles to produce this work as well as other documents.
• OTB-Documents/SoftwareGuide—LATEX files used to create this guide. (Note that the code
found in OTB/Examples is used in conjunction with these LATEX files.)
1.4.3 Documentation
Besides this text, there are other documentation resources that you should be aware of.
Doxygen Documentation. The Doxygen documentation is an essential resource when working
with OTB. These extensive Web pages describe in detail every class and method in the
system. The documentation also contains inheritance and collaboration diagrams, listing
of event invocations, and data members. The documentation is heavily hyper-linked to
other classes and to the source code. The Doxygen documentation is available on-line at
http://www.orfeo-toolbox.org/doxygen/.
Header Files. Each OTB class is implemented with a .h and .cxx/.txx file (.txx file for templated
classes). All methods found in the .h header files are documented and provide a quick way to
find documentation for a particular method. (Indeed, Doxygen uses the header documentation
to produces its output.)

42. 8 Chapter 1. Welcome
1.4.4 Data
The OTB Toolkit was designed to support the ORFEO Acompaniment Program and its associated
data. This data is available at http://smsc.cnes.fr/PLEIADES/index.htm.
1.5 The OTB Community and Support
OTB was created from its inception as a collaborative, community effort. Research, teaching, and
commercial uses of the toolkit are expected. If you would like to participate in the community, there
are a number of possibilities.
• Users may actively report bugs, defects in the system API, and/or submit feature requests.
Currently the best way to do this is through the OTB users mailing list.
• Developers may contribute classes or improve existing classes. If you are a developer, you
may request permission to join the OTB developers mailing list. Please do so by sending
email to otb “at” cnes.fr. To become a developer you need to demonstrate both a level of
competence as well as trustworthiness. You may wish to begin by submitting fixes to the OTB
users mailing list.
• Research partnerships with members of the ORFEO Acompaniment Program are encouraged.
CNES will encourage the use of OTB in proposed work and research projects.
• Educators may wish to use OTB in courses. Materials are being developed for this purpose,
e.g., a one-day, conference course and semester-long graduate courses. Watch the OTB web
pages or check in the OTB-Documents/CourseWare directory for more information.
1.6 A Brief History of OTB
Beside the Pleiades (PHR) and Cosmo-Skymed (CSK) systems developments forming ORFEO,
the dual and bilateral system (France - Italy) for Earth Observation, the ORFEO Accompaniment
Program was set up, to prepare, accompany and promote the use and the exploitation of the images
derived from these sensors.
The creation of a preparatory program1 is needed because of :
• the new capabilities and performances of the ORFEO systems (optical and radar high resolu-
tion, access capability, data quality, possibility to acquire simultaneously in optic and radar),
• the implied need of new methodological developments : new processing methods, or adapta-
tion of existing methods,
1http://smsc.cnes.fr/PLEIADES/A prog accomp.htm

43. 1.6. A Brief History of OTB 9
• the need to realise those new developments in very close cooperation with the final users for
better integration of new products in their systems.
This program was initiated by CNES mid-2003 and will last until 2010 at least It consists in two
parts, between which it is necessary to keep a strong interaction :
• A Thematic part
• A Methodological part.
The Thematic part covers a large range of applications (civil and defence ones), and aims at spec-
ifying and validating value added products and services required by end users. This part includes
consideration about products integration in the operational systems or processing lines. It also in-
cludes a careful thought on intermediary structures to be developed to help non-autonomous users.
Lastly, this part aims at raising future users awareness, through practical demonstrations and valida-
tions.
The Methodological part objective is the definition and the development of tools for the operational
exploitation of the future submetric optic and radar images (tridimensional aspects, change detec-
tion, texture analysis, pattern matching, optic radar complementarities). It is mainly based on R&D
studies and doctorate and post-doctorate research.
In this context, CNES2 decided to develop the ORFEO ToolBox (OTB), a set of algorithms encapsu-
lated in a software library. The goals of the OTB is to capitalise a methological savoir faire in order
to adopt an incremental development approach aimin to efficiently exploit the results obtained in the
frame of methodological R&D studies.
All the developments are based on FLOSS (Free/Libre Open Source Software) or existing CNES
developments.
OTB is implemented in C++ and is mainly based on ITK3 (Insight Toolkit):
• ITK is used as the core element of OTB
• OTB classes inherit from ITK classes
• The software development procedure of OTB is strongly inspired from ITK’s (Extreme Pro-
gramming, test-based coding, Generic Programming, etc.)
• The documentation production procedure is the same as for ITK
• Several chapters of the Software Guide are litterally copied from ITK’s Software Guide (with
permission).
• Many examples are taken from ITK.
2http://www.cnes.fr
3http://www.itk.org

44. 10 Chapter 1. Welcome
1.6.1 ITK’s history
In 1999 the US National Library of Medicine of the National Institutes of Health awarded six
three-year contracts to develop an open-source registration and segmentation toolkit, that eventu-
ally came to be known as the Insight Toolkit (ITK) and formed the basis of the Insight Software
Consortium. ITK’s NIH/NLM Project Manager was Dr. Terry Yoo, who coordinated the six prime
contractors composing the Insight consortium. These consortium members included three com-
mercial partners—GE Corporate R&D, Kitware, Inc., and MathSoft (the company name is now
Insightful)—and three academic partners—University of North Carolina (UNC), University of Ten-
nessee (UT) (Ross Whitaker subsequently moved to University of Utah), and University of Penn-
sylvania (UPenn). The Principle Investigators for these partners were, respectively, Bill Lorensen
at GE CRD, Will Schroeder at Kitware, Vikram Chalana at Insightful, Stephen Aylward with Luis
Ib´a˜nez at UNC (Luis is now at Kitware), Ross Whitaker with Josh Cates at UT (both now at Utah),
and Dimitri Metaxas at UPenn (now at Rutgers). In addition, several subcontractors rounded out the
consortium including Peter Raitu at Brigham & Women’s Hospital, Celina Imielinska and Pat Mol-
holt at Columbia University, Jim Gee at UPenn’s Grasp Lab, and George Stetten at the University of
Pittsburgh.
In 2002 the first official public release of ITK was made available.

45. CHAPTER
TWO
INSTALLATION
This section describes the process for installing OTB on your system. OTB is a toolbox, and as such,
once it is installed in your computer, provides by default a set of useful libraries. You can use these
libraries to build your own applications based on it. What OTB does provide, besides the toolbox,
is a large set of test files and examples that will introduce you to OTB concepts and will show you
how to use OTB in your own projects.
Since the release 3.12, OTB embeds a specific framework to generate applications in a more user-
friendly way. If you activate the specific option BUILD APPLICATIONS, OTB builds for each appli-
cation one shared library (also known as plugin). This plugin can be auto-loaded into appropriate
tools without recompiling, and is able to fully describe its own parameters, behaviour and documen-
tation.
The tools to use these plugins can be extended, but OTB is shipped with the following:
• A command-line launcher,
• A graphical launcher, with an auto-generated Qt interface, providing ergonomic parameters
setting, display of documentation, and progress reporting,
• A C and SWIG interface, which means that any application can be loaded, set up and executed
into a high-level language such as Python for instance.
The classical OTB powered applications are still available and will still be maintained:
Monteverdi An integrated application giving graphical access to a lot of OTB functionalities.
OTB-Wrapping Calling OTB from Python or Java (see chapter 34).
There are two ways to install OTB on your system: installing from a binary distribution, or compiling
from sources (Table 2.1). What you need depends on your system, and on what you intend to do.

46. 12 Chapter 2. Installation
OTB library and
internal applica-
tions
Monteverdi Wrapping (Java
and Python)
Any platform Build from source
(see section 2.2)
Build from source
(see section 2.2)
Build from source
(see section 2.2)
Windows 2000/X-
P/Vista/Seven
OSGeo4W installer
for internal applica-
tions
Windows or OS-
Geo4W installer
(see section 2.1.1)
OSGeo4W installer
(see section 2.1.1)
MacOS X 10.6 and
higher
MacPorts (see sec-
tion 2.1.2)
app’s DMG file (see
section 2.1.2)
Ubuntu Linux
10.04 and higher
(32/64 bits)
APT repository (see
section 2.1.3)
APT repository (see
section 2.1.3)
OpenSuse 11.X
and higher (32/64
bits)
RPM package (see
section 2.1.3)
RPM package (see
section 2.1.3)
CentOS 6.X and
higher (32/64 bits)
RPM package (see
section 2.1.3)
RPM package (see
section 2.1.3)
RPM package (see
section 2.1.3)
Table 2.1: Available installation procedures with respect to system configuration and target usage
2.1 Installing binary packages
2.1.1 Windows 2000/XP/Vista/Seven
For Windows 2000/XP/Vista/Seven users, there is a classical standalone installation program for
Monteverdi, available from the OTB download page. There are another way to install Monteverdi
directly through through OSGeo4W. With this new way, you can install other OTB packages as
described in the following paragraph.
Since version 3.12, we provide OTB packages through OSGeo4W for Windows 2000/XP/Vista/-
Seven users. Packages for the OTB applications, Monteverdi and OTB-Wrapping are available
directly in the OSGeo4W installer with the following names:
• otb-bin for command line and QT applications
• otb-python for python applications
• otb-monteverdi for the Monteverdi application
• otb-wrapping for low level Python/Java bindings.
Follow the instructions in the installer and select the packages you want to add. The installer will
proceed with the installation of selected packages and all their dependencies. In the case of otb-
monteverdi, Monteverdi will be directly installed in the OSGeo4W repository and a shortcut will

47. 2.1. Installing binary packages 13
be added to your desktop and in the start menu (in the OSGeo4W folder). You can now use directly
Monteverdi from your desktop, from the start menu and from an OSGeo4W shell with command
monteverdi. For the otb-bin packages, it will be available directly in the OSGeo4W shell, for
example run
otbgui_BandMath.
We recommended to use this way to install internal applications of OTB on Windows. If you want
to use the otb-python package, for example in QGIS, please following the install note found in the
OTB wiki. You can simply check from an OSGeo4W shell the list of available applications:
python
import otbApplication
print str( otbApplication.Registry.GetAvailableApplications() )
For more information you can read the OTB Cookbook which provides useful information about
these OTB applications.
2.1.2 MacOS X
Orfeo Toolbox is now available on MacPorts. The port name is called orfeotoolbox. You can follow
the MacPorts documentation to install MacPorts first, then install the orfeotoolbox port.
A standard DMG package is available for Monteverdi for MacOS X 10.8. Please go the the
OTB download page. Click on the file to launch Monteverdi.
2.1.3 Linux
Ubuntu 10.04 and higher
For Ubuntu 10.04 and higher, OTB, OTB applications, Monteverdi and OTB-Wrapping packages
may be available as Debian packages through APT repositories.
Since release 3.14.1, OTB packages are available in the ubuntugis-unstable repository.
You can add it by using these command-lines:
sudo aptitude install add-apt-repository
sudo apt-add-repository ppa:ubuntugis/ubuntugis-unstable
Now run:
sudo aptitude update

48. 14 Chapter 2. Installation
If you want only OTB libraries, please use:
sudo aptitude install libotb
If you want OTB Applications, please use:
sudo aptitude install otb-bin otb-bin-qt python-otb
If you want monteverdi application, please use:
sudo aptitude install monteverdi
If you want Python/Java wrapping, please use:
sudo aptitude install otb-wrapping-python otb-wrapping-java
If you are using Synaptic, you can add the repositories, update and install the packages through the
graphical interface.
For further informations about Ubuntu packages go to ubuntugis-unstable launchpad page and click
on Read about installing.
Moreover, nightly builds for all OTB projects are also available through APT repositories. However
you should use it carefully. If you are using apt command-line tools, use these command-lines to
add the otb repository to apt sources:
sudo aptitude install add-apt-repository
sudo add-apt-repository ppa:otb/orfeotoolbox-nightly
Now run:
sudo aptitude update
As with the previous cases, select which packages you will install.
sudo aptitude install libotb otb-bin otb-bin-qt python-otb monteverdi
Be careful not to add the two repositories, since they may cause incompatibilities.
apt-add-repository will try to retrieve the GPG keys of the repositories to certify the origin of the
packages. If you are behind a http proxy, this step won’t work and apt-add-repository will stall and
eventually quit. You can temporarily ignore this error and proceed with the update step. Following
this, aptitude update will issue a warning about a signature problem. This warning won’t prevent
you from installing the packages.

49. 2.1. Installing binary packages 15
OpenSuse 11.X and higher
For OpenSuse 11.X and higher, OTB, Monteverdi and OTB-Wrapping packages are available
through zypper.
First, you need to add the appropriate repositories with these command-lines (please replace 11.4
by your OpenSuse version):
sudo zypper ar
http://download.opensuse.org/repositories/games/openSUSE_11.4/ Games
sudo zypper ar
http://download.opensuse.org/repositories/Application:/Geo/openSUSE_11.4/ GEO
sudo zypper ar
http://download.opensuse.org/repositories/home:/tzotsos/openSUSE_11.4/ tzotsos
Now run:
sudo zypper refresh
sudo zypper install OrfeoToolbox
sudo zypper install OrfeoToolbox-devel
sudo zypper install Monteverdi
sudo zypper install OrfeoToolbox-python
Alternatively you can use the One-Click Installer from the openSUSE Download page or add the
above repositories and install through Yast Package Management.
In case you wish to test the latest version of the packages, you can run:
sudo zypper refresh
sudo zypper install OrfeoToolbox-beta
sudo zypper install OrfeoToolbox-beta-devel
sudo zypper install Monteverdi-beta
There is also support for the recently introduced ’rolling’ openSUSE distribution named ’Tumble-
weed’. For Tumbleweed you need to add the following repositories with these command-lines:
sudo zypper ar
http://download.opensuse.org/repositories/games/openSUSE_Tumbleweed/ Games
sudo zypper ar
http://download.opensuse.org/repositories/Application:/Geo/openSUSE_Tumbleweed/ GEO
sudo zypper ar
http://download.opensuse.org/repositories/home:/tzotsos/openSUSE_Tumbleweed/ tzotsos
and then add the OTB packages as shown above.

50. 16 Chapter 2. Installation
CentOS 5.5
Since 3.12 version, OTB packages (OTB, monteverdi) are available on CentOS 5.5 distribution.
In the following lines, we will describe the way to install OTB and monteverdi packages on this
distribution. If you want use OTB-Wrapping, please following the instructions found in this file.
Preliminary steps (common to all packages):
1. Configure your system to pass through your HTTP(S) proxy,
2. Add required extra repositories: EPEL, ELGIS and centosplus,
can be found in the previous file.
So if you want OTB and monteverdi packages, you need to install a standard RPM packages which
is available on OTB website:
wget http://www.orfeo-toolbox.org/packages/centos/5.5/i386/3.11.0/
gdal-1.8.0-5.i386.rpm
yum --nogpgcheck install gdal-1.8.0-5.i386.rpm
We can now get and install (replace version number by the current):
1. OTB libraries and applications package:
wget http://www.orfeo-toolbox.org/packages/centos/5.5/i386/3.11.0/
OrfeoToolbox-3.11.0-1.i386.rpm
yum --nogpgcheck install OrfeoToolbox-3.11.0-1.i386.rpm
2. monteverdi package:
wget http://www.orfeo-toolbox.org/packages/centos/5.5/i386/3.11.0/
Monteverdi-1.9.0-0.i386.rpm
yum --nogpgcheck install Monteverdi-1.9.0-0.i386.rpm
2.2 Building from sources
OTB has been developed and tested across different combinations of operating systems, compil-
ers, and hardware platforms including MS-Windows, Linux on Intel-compatible hardware and Mac
OSX. It is known to work with the following compilers: