Anti-noise computational ghost imaging based on dual-tree complex wavelet adaptive threshold denoising

Abstract In practical applications, the interference caused by noise in imaging systems cannot be ignored. This paper introduces a denoising approach for computational ghost imaging (CGI) that leverages the dual-tree complex wavelet transform with adaptive thresholding denoising in the prefabricated reference light source (RDTCWATGI). This method demonstrates superior noise resistance and effectively mitigates signal aliasing defects caused by wavelet threshold denoising (WTD). Simulation and experimental results indicate that, compared to WTD, using our method in CGI achieves effective noise reduction while ensuring the integrity of reconstructed results. As a post-processing technique, this denoising approach is simple to implement and enables image reconstruction in noisy environments, showing broad application prospects in practical GI applications.