Information saturation inmultispectral pixel level imagefusion

Abstract

The availability of imaging sensors operating in multiple spectral bands has led to the requirement of image fusion algorithms that would combine the image from these sensors in an efficient way to give an image that is more informative as well as perceptible to human eye. Multispectral image fusion is the process of combining images from different spectral bands that are optically acquired. In this paper, we used a pixel-level image fusion based on principal component analysis that combines satellite images of the same scene from seven different spectral bands. The purpose of using principal component analysis technique is that it is best method for Grayscale image fusion and gives better results. The main aim of PCA technique is to reduce a large set of variables into a small set which still contains most of the information that was present in the large