Compressive Sampling with Coefficients Random Permutations for Image Compression

The different image block has different sparsity or compressibility in transform domain; in general, the blocks in smooth region have stronger sparsity while those in texture or edge region have weaker sparsity. Based on this observation, a novel block DCT based sampling scheme with coefficients random permutations for image compressive sensing has been proposed in this paper. These random permutations make the sparsity of all the sampled blocks more evenly, which results in requiring approximate equal ratio of measurement for well reconstruction of each sampled block. Experimental results demonstrate that our proposed scheme can efficiently enhance the reconstructed image quality or reduce the measurement ratio.