Hyperspectral image contains more information which are gathered from numerous narrow wavebands from one or more regions, and large amount of data are huddled. An basic problems in hyperspectral image processing are dimension reduction, target detection, target identification, and target classification. In this document, we reviewed the latest activities of target classification, most frequently used techniques for dimension reduction, target detection. Hyperspectral image processing is a complicated process which rely on mixed agents. Here we also recognized and reviewed problems faced by some methods and to overcome the problems, current techniques are discussed and highlighted good methods. To improving correctness, genuine classification techniques and Detection Techniques analysis are recommended
Hyperspectral Image Dimension Reduction and Target Detection Based on Weighted Mean Filter and Manifold Learning
