PRINCIPAL COMPONENT ANALYSIS

BY

SWETHA. A

5WD12CGI15

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.

Run ERDAS . Open a viewer 1. Select “Interpreter” from toolbar. From interpreter select “Spectral

Enhancement". Further select “Principal Component” and window appears as shown.

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 .

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.

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

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

LAYER 3: O/P

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

COMBINATION OF ALL LAYERS

THANKS