Compressive coincidence counting imaging

The application of compressive sensing algorithm to coincidence-counting-based imaging is proposed. Coincidence counting imaging has the advantage that it can separate signals from classical stray light due to its quantum optical properties, which is not possible with conventional classical methods. However, coincidence counting imaging using EMCCD is significantly affected by noise and requires a huge number of images. The proposed method utilizes a compressive sensing algorithm and achieves a 2-4 times noise reduction in the mean noise level compared to a typical coincidence counting algorithm. Experimental results and statistical analysis results are presented.