A novel method for illumination suppression in hyperspectral images

Abstract

We have proposed a new method for illumination suppression in hyperspectral image data. This involves transforming the data into a hyperspherical coordinate system, segmenting the data cloud into a large number of classes according to the radius dimension, and then demeaning each class, thereby eliminating the distortion introduced by differential absorption in shaded regions. This method was evaluated against two other illumination-suppression methods using two metrics: visual assessment and spectral similarity of similar materials in shaded and fully illuminated regions. The proposed method shows markedly superior performance by each of these metrics.