Sequential color ghost imaging based on compressed sensing algorithm of post-processing measurement matrix

Abstract

Compressed sensing algorithm can be used in color ghost imaging to restore the image of object at the less demand of measurements times. However, the quality of the reconstructed color image is usually not satisfactory. In this paper, we propose a sequential color ghost imaging method that can complete color ghost imaging in a simple architecture and improve the quality of color image, which is optimize compressed sensing that can get better result of compressed sensing algorithm by post-processing the measurement matrix and establishing a new compressed sensing process. Under the condition of the same measurement times and reconstruction algorithm, compared with the unpost-processing one, the quality and detail of reconstructed image by the post-processing measurement matrix is quite improved especially with the increase of measurement times. Discussions on factors affecting the quality of the new compressed sensing process, such as the number of measurement and the detection noise intensity, are also conducted. Numerical simulation and physical experiment verified our proposed method.