Nonuniform Quantization For Block-based Compressed Sensing of Images In DPCM system

In practical signal processing, it is necessary to quantize the sampled signals. Quantization is considered a necessary step to digitalize signals and realize the high-efficient transmission of digital signals. There exists high correlation from one block to the next in the measurement domain for block-based compressed sensing of images. According to this feature, this paper employed differential pulse-code modulation to reduce the redundancy between two blocks, and which was coupled with nonuniform scalar quantization to provide quantized block-based compressed sensing of images. This paper analyzed the distribution of prediction errors in DPCM system and drew a conclusion that in statistical sense such distribution has a similar varying tendency with the characteristics of nonuniform scalar quantization. This discovery provided a theoretical basis for the proposed quantization method in this paper. Experimental results show that the proposed quantization scheme effectively increases the quantized signal to noise ratio, meanwhile improves the quality of image reconstruction.