Application of compressed sensing in ghost imaging system

Ghost Imaging(GI) provides a special method to get an image, when it is difficult using conventional methods. Which has become one of the hot topics in quantum optics recently. In this paper, we discuss the application of Compressed Sensing (CS) in GI system. We utilize the intensity distribution of the thermal light distributed like Gaussian distribution as the measurement matrix of CS, select the Discrete Cosine Transform (DCT) and Discrete Wavelet Transform (DWT) as the sparse matrix of the image object, adopt the Orthogonal Matching Pursuit (OMP) algorithm as CS reconstruction algorithm, and obtain the reconstructed image. The result shows that the quality of GI with CS using DCT and DWT has enhanced to more than 10dB in Peak Signal-to-Noise Ratio(PSNR) to the result with original GI algorithm when the compression rate is 0.5. At the same time, the quality of DCT-CS algorithm has a little improvement to that of DWT-CS algorithm.