RGB image processing based on compressed sensing

Compressed Sensing (CS) can project a high dimensional signal to a low dimensional signal by a random measurement matrix. In this paper, the signal reconstruction algorithm of Compressed Sensing is discussed and a new method is proposed to improve the speed of reconstruction and the quality of recovered images through the orthogonalization of measurement matrix based on proximate QR factorization row matrix. Here we use a M × N dimensional matrix Φ to complete the signal from high dimensional to low dimensional .In experiment, the RGB image is processed by the improved measurement matrix and OMP algorithm. The results show that the processing of image reconstruction would be fewer amounts of calculation and reducing the effect of the image reconstruction speed.