Edge-preserving nonlocal weighting scheme for total variation based compressive sensing recovery

Although total variation minimization technique is being widely used in compressive sensing recovery, it still suffers from the so called staircase artifact which is caused by losing fine details of image. As a solution for the problem, in this paper, we propose an edge-preserving weighting scheme utilizing nonlocal structure and histogram of natural image in the gradient domain. Experimental results show that the proposed scheme surpasses the traditional total variation and the edge-guided CS in both objective and subjective qualities.