Abstract:

The performance of image compressive sensing (CS) recovery algorithms degrades seriously in the presence of noise. Structured prior information and side information are simultaneously utilized to enhance the robustness of the approximate message passing (AMP) algorithm to noise. The low-rank property of similar patches is exploited to capture low-rank subspace structures. The reconstructed image in the previous iteration that contains some identified components is taken as side information to enhance details. Comparing with the original AMP algorithm and the proposed method without the aid of side information, the proposed method averagely improves peak signal to noise ratio (PSNR) by 3.89 dB and 0.27 dB while producing clearer and more detailed images respectively.