Applied Mathematics & Information Sciences

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Based on compressed sensing, a new bit-plane image coding scheme was presented. Due to different important for different image bit-plane, the new method is robust to bit error, and has the advantages of simple structure and easy software and hardware implementation. Because the values of the image bit-plane are 1 or zero, one order difference matrix was chosen as sparse transform matrix, and the simulation show that it has more sparse presentations. For the general 8-bit images, its have 8 Bit-plane, eighth Bit-plane is Most Significant Bit-plane, so we can adopt more measure vectors for reconstruction image precision. At the same time, this kind of image codec scheme can meet many application demands. The method partitioned an image into 8 bit-plane, and made the orthogonal transform using the one order difference matrix for each bit plane, and then formed multiple descriptions after using local Hadamard Matrix measurements of each bit plane. At decoding end, it reconstructed the original image approximately or exactly with the received bit streams by using the Orthogonal Match Pursuit (OMP) algorithms. The proposed method can construct more descriptions with lower complexity because the process of bit plane data measuring is simple and easy to hardware realize. Experiment results show that the proposed method can reconstruction image with different precision and it can easily generate more descriptions.

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