Experimental Investigation of Iterative Pseudoinverse Ghost Imaging

Abstract

An iterative pseudoinverse ghost imaging (IPGI) method is proposed based on iterative denoising and pseudoinverse ghost imaging (PGI). The background noise in the imaging is eliminated in iterations by setting an appropriate threshold. The IPGI method provides a significantly larger enhancement of the peak signal-to-noise ratio (PSNR) than the PGI technique for binary objects. Experiments and data analyses are performed to evaluate the performance of the proposed method. Compared with conventional GI, differential GI, and PGI methods, the proposed method has the highest performance in visual effects and significantly improves the imaging quality. For a certain PSNR, the proposed method provides satisfactory performance in terms of computing time.