Background dictionary construction-based sparse representation hyperspectral target detection - Tao Yang; Lin Feipeng; Yang Wen; Weng Shan (Dianzi Jishu Yingyong)
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.