Abstract
Block Compressive Sensing (BCS) is a image reconstruction model based on CS theory. By use the same measurement matrix to obtain the data in the form of Block × Block. Algorithm meaning to solve the problem that the traditional CS measurement matrix required for large storage, but different block has important influence on reconstruction time and effect. In this paper, find out the optimum parameters of the block. By compared the PSNR and reconstructed image effect under different sampling rate and different block sizes.
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