Camouflage Target Recognition Based on Dimension Reduction Analysis of Hyperspectral Image Regions

Abstract

Hyperspectral reconnaissance technology can realize three-dimensional reconnaissance by using target space and spectral information, which effectively improves the efficiency of battlefield reconnaissance. However, in order to obscure what is true and what is false to confuse the enemy, camouflage technology is also developing. Hiding the target in the background environment and setting false targets have become common camouflage procedures on the battlefield. The camouflaged target has very similar spatial and spectral characteristics to the real target, so the method of identifying the camouflaged target according to the similarity threshold of the original spectral data is no longer reliable. In order to solve the problem of high spectral similarity and low discrimination between a camouflaged target and a real target in a hyperspectral image, a joint processing method of spatial spectrum information is adopted in this paper. Firstly, the hyperspectral image is preprocessed, and then the target area to be measured is determined. Finally, the dimensions of the determined sensitive small area are reduced. Experiments show that this processing method can effectively reduce the spectral similarity of true and false targets, increase the spectral difference of true and false targets and improve the ability to identify true and false targets based on hyperspectral images.