PCA

1. PRINCIPAL COMPONENT
ANALYSIS
BY
SWETHA. A
5WD12CGI15

2. DEFINITION

It’s a mathematical procedure that uses orthogonal
transformation to convert a set of observations of
possibly correlated variables into a set of values of
linearly uncorrelated variables called principal
components.

3. Run ERDAS .
 Open a viewer 1.
 Select “Interpreter” from toolbar.
 From interpreter select “Spectral Enhancement".
Further select “Principal Component” and window
appears as shown.


5. 



Open the input file and specify the output
Number of components desired as 4
Mention the output file matrix.
Press ok and modeler runs as shown .

6. 

While selecting each layers, open the output file, single
click, go to raster options, change “display as:’ gray scale and
layer as 1.
Similarly repeat the above procedure to view individual layers.

7. LAYER 1: O/P:URBAN AREA AND WATER
REGIONS ARE HIGHLIGHTED.

8. LAYER 2: O/P: VEGETATION REGIONS ARE
HEIGHTENED .

9. LAYER 3: O/P

10. LAYER 4: O/P: ALL FEATURES ARE HIGH
LIGHTENED AND IMAGE IS BLUR.

11. COMBINATION OF ALL LAYERS

12. THANKS