Robust Correspondence Imaging Against Random Disturbances With Single-Pixel Detection

Abstract

Random disturbance has become a great challenge for correspondence imaging (CI) due to dynamic and nonlinear scaling factors. In this paper, we propose a robust CI against random disturbances for high-quality object reconstruction. To remove the effect of dynamic scaling factors induced by random disturbance, a wavelet and total variation (WATV) algorithm is developed to estimate a series of varying thresholds. Then, light intensities collected by a single-pixel detector are processed by using the series of estimated varying thresholds. To realize high-quality object reconstruction, the binarized light intensities and a series of random patterns are fed into a plug-and-play priors (PnP) algorithm with an iteration framework and a general denoiser, called as CI-PnP. Theoretical descriptions are given in detail to reveal the formation mechanism in CI under random disturbance. Optical measurements are conducted to verify robustness of the proposed CI against random disturbances. It is demonstrated that the proposed method can remove the effect of dynamic scaling factors induced by random disturbance, and can realize high-quality object reconstruction. The proposed method provides a promising solution to achieving ultra-high robustness against random disturbances in CI, and is promising in various applications.