Abstract: A block compressed sensing method is proposed considering that the calculation time of image reconstruction increases rapidly with the image size when compressive sensing (CS) theory is applied in single-pixel imaging. In the method, a digital micro-mirror device (DMD) and a multi-element detector array are used for encoding and measuring, and a total variation minimization method is used for image reconstruction, where the peak signal-to-noise ratio (PSNR) and the structural similarity (SSIM) of recovered images are improved by using gray stretch technique. Simulation results show that the method has the characteristics of shorter calculation time and higher recovered image quality. For 16 image blocks, the calculation time can be shorten by 40% at least. The PSNR and mean SSIM values of recovered images can be improved by 70% and 11%, respectively, through gray stretching of image blocks.

Key words: information processing, compressive sensing, sparse representation and reconstruction, multi-element detector array, total variation minimization with quadratic constraints, total variation minimization with equality constraints