Image reconstruction based on compressive sensing using optimized sensing matrix

This paper discusses Measurement Matrix Optimization problem in Compressive Sensing (CS). The objective of Measurement Matrix Optimization in CS is to minimize the mutual coherence between Measurement matrix and Sparse representation basis. Optimization also improves the image recovery performance. In order to optimize the measurement matrix, a simulated annealing based optimization method is proposed. Results shows that Compressive Sensing with optimized measurement matrix can achieve better PSNR values than one with un optimized matrix.