Compressive color ghost imaging based on pseudo-inverse matrix

Abstract

Abstract In this paper, a compressive color ghost imaging method based on pseudo-inverse matrix is proposed, which improves the quality of imaging result via post-processing the measurement matrix. For a color ghost imaging utilizing compressive sensing algorithm, if we treat a color image as a form of grayscale image and perform pseudo-inverse operation on the measurement matrix, a new measurement model will be established and the preliminary ghost imaging reconstruction result can be obtained by the compressive sensing algorithm, then the preliminary result is converted into a superposition of three channels to form the final color image. The feasibility of this method is proved by numerical simulation and physical experiment, and comparations among our method and the latest typical improvement methods, i.e., the singular value decomposition compressive ghost imaging and the pseudo-inverse ghost imaging, are conducted. The results show that our method can achieve the better quality of reconstructed color image with a high structure similarity beyond 0.8.