Robust compressed ghost imaging against environmental influence factors

Ghost imaging based on sparse sampling is sensitive to the environmental influence factors frequently encountered in practice, such as instrumental drift and ambient light change, which could cause degradation of image quality. In this manuscript, we report a robust compressed sensing technique which could effectively reduce the influence of measurement errors on image quality. For demonstration purposes, we implement the proposed technique to ghost imaging, namely differential compressed sensing ghost imaging (DCSGI). By applying differential measurements n times, the first n Taylor expansion polynomials of the error could be eliminated in n -order DCSGI. It has been verified theoretically and experimentally that DCSGI works well with typical errors which exists in the realities of ghost imaging applications, while the conventional approach can hardly. In addition, the proposed technique may also replace conventional compressed sensing in other applications for anti -interference high -quality reconstruction. (c) 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement