PAN-SHARPENING BY PCA ON WPM/CBERS-04A IMAGES USING A SINGLE MATRIX ON DIFFERENT IMAGES: A CASE STUDY

Pan-sharpening techniques are commonly used to integrate multispectral and panchromatic images. Finding the appropriate algorithm is one that maintains the spectral and spatial information content of the input images is a challenge. Principal component analysis (PCA) is one of these techniques. Therefore, the objective of this work was to evaluate the possibility of determining a single PCA matrix for pan-sharpening a heterogenous set of images. The results indicate that a single PCA matrix generates products with worse spectral quality compared to the hybrid images generated by the fine-tuned PCA matrix.