Small infrared target detection based on improved structure collaborative sparseness

Aiming at the problem of small infrared target detection, improved structural collaborative sparseness (ISCS) detection algorithm which combined sparseness and edge-preserve smoothing was put forward. Firstly, in order to improve the background, component of bigger gradient was extracted based on zero norm of gradient; Secondly, background sparseness was modeled by row norm; At last, small dim infrared target was located by column norm of error matrix. Against other detection algorithms, results of experiments show that ISCS detection algorithm can explore relationships between pieces of background, restrain clutter and enhance performance of the small dim infrared target detection algorithm against complex environment.