2. Light and Color
• Light
– Electromagnetic Wave
– Wavelength 380 to 780 nanometers (nm)
• Color
– Depend on spectral content (wavelength
composition)
– E.g. Energy concentrated near 700 nm appears red.
• Spectral color is light with a very narrow
bandwidth.
• A white light is achromatic.
3. Color
• Two types of light sources
– Illuminating light source
– Reflective light source
4. Light Sources
• Emits light (e.g. sun, bulb, TV)
• Perceived color depends on
spectral contents of the emitted
light
• Follows the additive rule: (the
perceived color of several mixed
illuminating light sources depends
on the sum of the spectra of the
light sources)
Illuminating Source Reflecting Source
• Reflects incoming light (e.g. all non-
illuminating objects)
• Perceived color depends on
spectral contents of the reflected
light
• Follows the subtractive rule: (the
perceived color of several mixed
reflective light sources depends on
the remaining (unabsorbed)
wavelengths)
5. Color
• Illuminating light source generates
– Light of certain wavelength, or
– Light of a wide range of wavelength
– Follow additive rule:
• Color of the mixed light depends on the SUM of
the spectra of all the light sources
6. Color
• Examples of illuminating light sources of
wide wavelengths
– Sun, stars
– Light bulb, florescent tube
• Examples of illuminating light sources of
narrow wavelength
– Halogen lamp, Light power light bulb
– Phospher, Light Emitting Diode
7. Color
• Reflecting light
– Object absorbs incident light of some wavelengths
– Object reflects incident light of remaining
wavelengths
– E.g. An object that absorbs wavelengths other than
red would appear red in color
– Follow subtractive rule: color of the mixed reflecting
light sources depends on the remaining unabsorbed
wavelengths
8. Color
• Examples of reflecting light source
– Mirror and white objects reflects all
wavelengths of light regularly
– Most solid objects
– E.g. Dye, photos, the moon
9. Understanding Human Vision
System (HVS), Why?
• Image is to be SEEN!
• Perceptual Based Image Processing
– Focus on perceptually significant information
– Discard perceptually insignificant information
• Issues:
– Biological
– Psychophysical
12. Eye Anatomy
•Cornea is the eye's window to the
outside world.
•A biological, composed of tissue is
transparent similar to a glass
windows.
•Iris controls the amount of light
entering the eye by adjusting the size
of the pupil in a tenth of a second.
14. Eye Function
• Eye can function only if
cornea, iris, pupil, lens,
choroid, sclera, retina,
muscles, fovea and optic
nerves are present at the
same time, in their correct
positions.
• This is why it's impossible
for the eye to have
developed gradually, over a
period of time.
15. Human Perception of Color
• Retina contains two classes of receptors:
– Cones (6-7 millions):
• Each one connected to its own nerve end
• Day vision, can perceive color tone
• red cone, green cone, and blue cone
– Rods (75-100 millions):
• Several rods are connected to a single nerve
• Very sensitive to intensity of light
• Generates monochromatic response
• Night vision, perceive brightness only
16. Human Vision System
• Each part of our eye has some functions
– Iris controls the intensity of light entering the eye
– Circular muscle controls the thickness of the lens
– Lens refracts the light onto the fovea
– Optic nerve transmits light signals to the brain
• Brain
– interprets the light signals from both eyes
– understands the signals as an image
17. Path of light in the human eye
– Enters eye through cornea
– Passes through hole within iris
– Refracted by the lens
– Hits the retina wall inside the eye
– Excites some light-sensitive cells
Opti
c
nerv
e
Fovea
Retina
Cornea
Iris
LensCircular
muscle
18. Image Capturing and Formation
• An image is formed by the capture of
radiant energy that has been reflected
from surfaces that are viewed
• The amount of reflected energy, f(x,y), is
determined by two functions:
– The amount of light falling on a scene, i(x,y)
– The reflectivity of the various surfaces in the
scene, r(x,y)
• These two functions combine to get
f(x,y) = i(x,y) * r(x,y)
19. Image Formation Model
f(x,y)= i(x,y) r(x,y)
0<f(x,y)<∞
0<i(x,y)<∞
0<r(x,y)<1 reflectance
illumination
Intensity – proportional to energy
radiated by a physical source
20. Image Formation in the Eye
Focal length: 14-17mm Length of tree image≅2.55mm
For distant objects (>3m), lens exhibits the least refractive power (flattened)
For nearby objects (<1m), lens is most strongly refractive (curved)
• Distance between center of lens and retina (focal length) vary
between 14-17 mm.
• When object is 3 m or more away, f = 17mm with lowest refractive
power.
• Image length h = 17(mm) x (15/100)
21. Image Quality Measurement
• Objective measurements
– Measured by instruments
– Invariant to the change of subjects
– Peak Signal to Noise Ratio (PSNR)
• Subjective measurements
– Measured by human beings
– Variant to the change of subjects
– Human survey
22. Objective Image measurements
• Signal-to-Noise Ratio
– Signal-to-Noise Ratio (SNR) is the ratio of the
signal to the noise
– It is often measured in decibels (dB) as
• Peak Signal-to-Noise Ratio (PSNR)
– The ratio of the maximum value of the signal to the
measured noise amplitude (in dB).
1020log
signal
SNR
noise
=
max
1020log
measured
signal
PSNR
noise
=
24. Brightness Adaptation
• HVS can view large intensity range (1010
)
• HVS cannot operate over such a high dynamic
range simultaneously,
• If one is at Ba intensity (outside) and walk into
a dark theater, he can only distinguish up to
Bb. It will take much longer for eye to adapt for
the scotopic vision to pick up.
• But accomplish such large variation by
changes in its overall sensitivity, a
phenomenon called “brightness adaptation”
25. Brightness Discrimination
Weber ratio=∆I/I
• HVS’s sensitivity to intensity
difference differ at different
background intensities.
• Weber ratio: ∆I/I: Just
noticeable intensity
difference versus
background intensity. It is a
function of log I.
26. Simultaneous Contrast
The perceived brightness of inner square are different due to different
background intensity levels even they are identical.
Same luminance but varying brightness (perceived luminance)
29. Temporal Vision
• Perceived spatial resolution reduced
sharply at scene change
• Flicker fusion: the basis of movie and TV
• Eye is more sensitive to flicker at high
luminance than low luminance.
30. Frequency Threshold Vision
• Using spatial grating, it is found that
contrast sensitivity is a function of spatial
and temporal frequencies.
• In general, the contrast sensitivity
decreases as spatial and temporal
frequencies increases.
31. Lightness Illusion
If we cover the right side of the figure and view the
left side, it appears that the stripes are due to paint
(reflectance). If we cover the left side and view the
right, it appears that the stripes are due to different
lighting on the stair steps (illumination).
37. Image Resolution
• 3 resolutions
1. Spatial resolution (no. of pixels)
2. Brightness (no. of grey levels)
3. Temporal (number of frames per second)
• These resolutions do have a mutual
dependency
39. Spatial Resolution
• An image is represented as a 2-D array of sample points called
pixels.
• A simple definition of spatial resolutions
spatial resolution = h * v
where h = no. of horizontal pixels and v = no. of vertical pixels.
• E.g. A 320 x 200 image has 320 pixels on each horizontal line and
200 pixels on each vertical line.320
x x x x x x x x x x x x x x x x x x x
x x x x x x x x x x x x x x x x x x x
x x x x x x x x x x x x x x x x x x x
x x x x x x x x x x x x x x x x x x x
x x x x x x x x x x x x x x x x x x x
x x x x x x x x x x x x x x x x x x x
x x x x x x x x x x x x x x x x x x x
pixel
200
40. Spatial Resolution
• Field of view, θv : the angle subtended by rays of
light that hit the detector at the edge of the
image
• Relationship between field of view, the camera
detector, and focal length, f.
• r: the smallest resolvable object
• Z: the distance from the camera
• θ: the angular resolution in radians
θv
f
v
h
r
Z
θ =
41. Spatial Resolution
• To resolve an object 2mm in diameter at
a range of 1m, the minimum angular
resolution, θ, needs to be
θ = 2mm/1m
= 0.002 radian
= 0.1146 degree.
42. Spatial Resolution
• According to Nyquist theorem, at least
two samples per period are needed to
represent a periodic signal
unambiguously,
• Applying the Nyquist theorem to the
spatial dimension, two pixels must span
the smallest dimension of an object in
order for it to be seen in the image.
43. Spatial Resolution
• When a fixed size displaying window shows
an image of varying resolution
– Low resolution image loses details
– High resolution image shows details
Low resolution High resolution
46. Brightness Resolution
• For monochrome image,
– Brightness resolution = Number of grey
levels
• Our eyes can differentiate around
40 shades of grey only
• Image capture devices are limited in
differentiating number of grey levels
• Most monochrome images are
captured using 8 bit values. Range
of grey levels is [0, 255].
• Images with more shades of grey
b&w
8 bit grey
48. Color Resolution
• For color images, a display
device may use fewer
colors
– Color resolution = number of
distinguishable colors
• Color images are captured
using three eight bit
values.
• Images with more colors
show image with high
fidelity
8 bit color
24 bit color
49. Image Bits per Pixel
• 1 bit/pixel: black & white image, facsimile
image
• 4 bits/pixel: computer graphics
• 8 bits/pixel: greyscale image
• 16 or 24 bits/pixel: colour images
– colour representations: RGB, HSV, YUV,
YCbCr
50. 1-bit Images
Each pixel is stored as a single
bit (0 or 1)
Also called, 1-Bit / binary
image / bi-level/ two-level/
B&W/ Monochromatic /
monochrome (since it contains
no color)
640x480 monochrome image
requires 38.4 kB of storage
(640x480/8).
51. Grey-scale image
Each pixel has a gray-value
between 0 and 255.
Each pixel is represented by a
single byte; e.g., a dark pixel
might have a value of 10, and a
bright one might be 230.
8 bit image can be thought of as a
set of 1-bit biplane.
A 640x480 grayscale image
requires 300 kB of storage
(640x480=307,200)
52. Image Data Types
• The most common data types for graphics and image
file formats - 24-bit color and 8-bit color.
• Most image formats incorporate a compression
technique due to the large storage size of image files.
Compression techniques either lossless or lossy.
• In a color 24-bit image, each pixel is represented by
three bytes, usually representing RGB.
• Many 24-bit color images are actually stored as 32-bit
images, with the extra byte of data for each pixel used
to store an alpha value representing special effect
information (e.g., transparency).
53. 8-Bit Color Images
• Some systems support 8 bits of color information in
producing a screen image
• 8-bit color images store only the index, or code value, for
each pixel. Then, e.g., if a pixel stores the value 25,
means go to row 25 in a color look-up table (LUT).
54. Image Capture
• Images may be captured using
– Cameras
– Video cameras
– Fax machines
– Ultrasound scanners
– Radio telescopes
• An image is formed by the capture of radiant
energy that has been reflected from surfaces that
are viewed
• Cameras main types:
– Vidicons, charge coupled devices (CCDs), and
Complementary Metal Oxide Silicon (CMOS).
55. Image Capture
• The range is practically bounded by the
hardware resolution. It is calibrated to 0
for black and to 255 for white.
Intermediate values are different
intensity of grey.
Image called “Lena” by
multimedia scientists - this is a
standard image used to
illustrate many algorithms.
56. Image Capture
A color image is
formed by combining
the 3 images captured
by the red, blue, and
green sensors.
Red sensor Green sensor Blue sensor
57. Image Sensing
• Photographic Sensor: an image is typically
proportional to the radiant energy received in the EM
band to which the sensor/detector is sensitive. Image
called Intensity image.
• Tactile Sensor: an image is typically proportional to
the sensor deformation caused by the surface of or
around of an object.
58. Image Sensing
• Range Finder sensor: an image is a function of the line-of-
sight distance from the sensor position to an object in the 3-D
world. This image is called range image
• Thermal Imaging: Thermographic cameras detect in the IR
range of EM spectrum and produce images of that radiation.
• IR radiation emitted by all objects based on their
temperature.
• Thermography makes it possible to see one’s environment
with or without visible illumination.
• Ex. Military application; firefighters, maintenance
operations, etc.
65. Digital Image
a grid of squares,
each of which
contains a single
color
a grid of squares,
each of which
contains a single
color
each square is
called a pixel (for
picture element)
each square is
called a pixel (for
picture element)
Color images have 3 values per
pixel; monochrome images have 1
value per pixel.
69. Digital Image Formation:
Quantization
continuous color input
discretecoloroutput
continuous colors
mapped to a finite,
discrete set of colors.
continuous colors
mapped to a finite,
discrete set of colors.
71. Commonly–used Terminology
Neighbors of a pixel p=(i,j)
N4(p)={(i-1,j),(i+1,j),(i,j-1),(i,j+1)}
N8(p)={(i-1,j),(i+1,j),(i,j-1),(i,j+1),
(i-1,j-1),(i-1,j+1),(i+1,j-1),(i+1,j+1)}
Adjacency
4-adjacency: p,q are 4-adjacent if p is in the set N4(q)
8-adjacency: p,q are 8-adjacent if p is in the set N8(q)
Note that if p is in N4/8(q), then q must be also in N4/8(p)
From http://www.stlukeseye.com/Anatomy.asp
The eye is nearly a sphere, with an average diameter of approximately 20 mm.
Iris: contracts or relaxes to control the amount of light going into the eye.
Pupil: Central opening of the iris. It varies in diameter from approximately 2 to 8 mm.
Lens: Its degree of convexity varies with the closeness of the scene to focus the image on the retina
Retina: The innermost membrane of the eye, which lines the inside of the wall’s entire posterior portion. Pattern vision is afforded by the distribution of discrete light receptors over the surface of the retina.
From http://www.macula.org/anatomy/retinaframe.html
