Plants Change Detection in Forest Areas based on Satellite Imagery using Kernel MNF

In this paper, proposes an efficient method for change detection in forest areas using panchromatic stereo imagery and Multispectral imagery using kernel minimum noise fraction analysis. Due to low spectral information it is difficult to extract the change features, since changes mostly occur together with other unrelated changes such as environmental changes and seasonal changes. Hence the kernel minimum noise factor approach is used to transform the image of simple dimension to high dimensional feature space using centering followed by computation of Eigen values and Eigen vectors of the given image. Image subtraction extracts the surface variation information from the two different input images. Images are classified and