ASPL-APBT Algorithm for Block Compressed Sensing Image Reconstruction

Based on the block compressed sensing (BCS) framework, a new and non-orthogonal transform named all phase biorthogonal transform (APBT) is introduced to exploit the image sparsity, reduce the encoding complexity and be applicable to the blocked image easily. APBT exploits the signal sparsity better than DCT, and meanwhile it overcomes the defects of multiscale transform such as wavelet transform with high computational complexity and the feature of not being applicable to the blocked image. In order to improve the efficiency of BCS reconstruction, the accelerated smoothed projected Landweber (ASPL) iteration algorithm is put forward. Combined with the sparse constraints in APBT, the BCS-ASPLAPBT reconstruction algorithm is advanced. Experimental results demonstrate that the proposed algorithm outperforms the method of using DCT sparsifying coupled with common SPL iteration not only in the aspect of PSNR, but in terms of the reconstruction time and the iteration number.