Abstract:

A novel fractal compressive sensing (CS) imaging method is proposed in this paper for solving some bottlenecks of CS application in remote sensing imaging. On the one hand, multi-scale lens would be used to reduce the massive computation cost, which is caused by the traditional CS imaging based on sparse representation under large field of view. On the other hand, l1-norm minimization, as the object function of traditional CS imaging, is replaced by fractal dimension for improving the quality of middle and high resolution remote sensing imaging in image details. Experimental results show that, multi-scale fractal CS imaging method can not only meet the timeliness requirement of remote sensing imaging but also improve the imaging quality in details level.

Key words: compressed sensing, remote sensing imaging, multi-scale lens, l1-norm minimization, fractal dimension