Anomaly Detection in Hyperspectral Imagery

Abstract

In this chapter we are presenting the literature and proposed approaches for anomaly detection in hyperspectral images. These approaches are grouped into four categories based on the underlying techniques used to achieve the detection: 1) the statistical based methods, 2) the kernel based methods, 3) the feature selection based methods and 4) the segmentation based methods. Since the first approaches are mostly based on statistics, the recent works tend to be more geometrical or topological especially with high resolution images where the high resolution implies the presence of many materials in the same geographic area that cannot be easily distinguished by usual statistical methods.