Block Compressive Sensing Algorithm Based on Interleaving Extraction in Contourlet Domain
نویسندگان
چکیده
Abstract: We propose a block image compressive sensing algorithm based on interleaving extraction in Contourlet domain to improve the performance of image sparse representation and quality of reconstructed images. First, we propose the interleaving extraction scheme and partition an image into several sub-images using interleaving extraction. Second, we represent the sub-images in Contourlet domain and measure Contourlet sub-band coefficient matrices using different dimensional Gaussian random matrices. Finally, we rebuild the sub-band coefficients with the orthogonal matching pursuit algorithm and conduct Contourlet inverse transform to reconstruct the original images. Experimental results show that the subjective visual effect and peak signal to noise ratio of the proposed algorithm are superior to those of the original compressive sensing algorithms under the same sampling rate.
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