High-quality compressed sensing imaging with limited detector bits using sparse measurements and multiple dithers

High-flux measurement characteristics of compressed sensing (CS) imaging causes the imaging system prone to be disturbed by quantization. To realize high-quality CS imaging with limited detector bits, an improved imaging method combining sparse measurements and multiple dithers is proposed to reduce the dynamic range of the measured signals and increase that of effective detection. Simulations and experiments show that compared with traditional CS imaging, the proposed system decreases reconstruction errors caused by quantization distortions and may reduce the required number of detector bits to 1. The effects of detector noise and system parameters are discussed to validate the feasibility and performance of this method.