Principal Components Analysis
Principal Component Analysis (PCA) aims to eliminate the interband correlation and the effective dimensionality of the data or image. The false color composite of the original Laguna.img file appears below. Fig. 1: Standard color infrared composite image The satellite image from Google Earth of Los Banos, Laguna was also included for identification of features and their names. Fig. 1a shows the saved image. Fig.1a: Google Earth image of Los Banos, Laguna After subjecting the original image to principal components analysis, a color composite using PC1,PC2,PC3 as R,G,B respectively was produced. The color composite image was shown in the figure that follows. Fig. 2: RGB = PC1,PC2,PC3 of Laguna.img The six principal component grayscale images appear below. Fig. 3: Output principal component images The tonal patterns of the principal component image 1 differ with that of ETM+ band 1 of Laguna.img. Figure 4 shows the a generlized view of the sa...