Compressive sensing ghost imaging based on image gradient

In order to improve the imaging quality of ghost imaging and solve the problem of high distortion at a low sampling rate, the compressive sensing ghost imaging based on image gradient (IGGI) is proposed. The image gradient can reflect the changes of optical characteristics and carry the edge information of object. In this paper, the principle of compressive sensing ghost imaging is analyzed. And the total variation, the integral of image gradient, is used to optimize the reconstruction process. Simultaneously, the threshold of matching degree is set up to reduce computation load and improve imaging speed. The results of simulation and experiments show that compared with traditional ghost imaging, the IGGI can achieve high-quality images and obtain the edge information of targets at a low sampling rate, which further facilitate the practical application of ghost imaging.