![]() ![]() Then, we propose a relative peak signal-to-noise ratio (PSNR) model for evaluating distortion, which reveals the relationship between relative PSNR, sampling rate, and bit-depth. The bit-rate model reveals the relationship between bit rate, sampling rate, and bit-depth. In this paper, we first present a bit-rate model that considers the compression performance of CS, quantification, and entropy coder. In circumstances where the bit budget for image transmission is constrained, knowing how to choose the sampling rate and the number of bits per measurement (bit-depth) is essential for the quality of CS reconstruction. In engineering practices, the resulting CS samples are quantized by finite bits for transmission. ![]() Compressed sensing (CS) offers a framework for image acquisition, which has excellent potential in image sampling and compression applications due to the sub-Nyquist sampling rate and low complexity. ![]()
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