Improving Compressed Sensing Image Reconstruction Based on Atmospheric Modulation Using the Distributed Cumulative Synthesis Method

The problem of long-distance imaging through time-varying scattering media, such as the atmosphere, is encountered in many science fields. Recent studies have demonstrated that random atmospheric variability can be considered a spatial light modulator compressed sensing imaging. However, quality reconstructed image needs to further improved. In this paper, we propose distributed cumulative synthesis method improve reconstruction based on modulation. For multiple original images various types, simulation experiment with different sampling rates was conducted using method. results show that, compared single source, effectively image, whether it full or undersampling. addition, sparsity impact factor defined quantify ability measurement matrix obtained by This value used an evaluation index for optimized design Noise analysis shows proposed has better anti-noise performance than source