Detail-preserving compressive sensing recovery based on cartoon texture image decomposition

In this paper, we propose a detail-preserving reconstruction method for total variation-based recovery in low subrate compressive sensing using cartoon texture image decomposition and residual reconstruction. It iteratively decomposes and reconstructs cartoon and texture image components separately. A nonlocal structure-preserving filter is utilized to reduce staircase artifacts while preserving nonlocal structures of image in the spatial domain. Experimental results show that the proposed method outperforms the conventional ones in terms of preserving small scale details of image.