Parallel compressive ghost imaging based on threshold segmentation

To improve the speed of ghost imaging, the parallel compressed differential ghost imaging method is proposed based on threshold segmentation (TS-PCGI). Firstly, the large fluctuation of sampled data is selected by setting a reasonable threshold. Secondly, parallel computing divides the image into four parts. Finally, the image is restored through compressed sensing reconstruction algorithm. The results of a semi-physical simulated figure “BUAA” and experimental object "light" show that this method can restore the object image with less sampling and time compared with conventional second-order correlated imaging. The signal noise ratio is improved.