School of Communication and Information Engineering,，Chongqing University of Posts and Telecommunications， Chongqing 400065,，China
Abstract： Aiming at the existing target detection algorithms based on sparse representation, in the process of building the background dictionary with concentric double windows, the target pixels will interfere with the background dictionary. A sparse representation hyperspectral target detection algorithm based on background dictionary is proposed. The algorithm decomposes the hyperspectral image into low rank background and sparse target, and introduces the target dictionary as the prior information of sparse target, which can separate the target and background better and construct a pure background dictionary. Simulation results on four public hyperspectral image datasets show that the proposed algorithm has excellent detection performance.
Key words : hyperspectral image,；sparse representation；binary-class,；target dictionary；low-rank
