Preprocessing method for underwater time-gated SPAD-array-based images utilizing Retinex and BM3D

Underwater optical imaging is affected by light absorption and backscattering in water, thus yielding low signal-to-noise ratios and limited imaging ranges. This study proposes an image preprocessing method for underwater, time-gated, single-photon avalanche diode (TG-SPAD)-array-based images according to the Retinex theory, and a block-matching and 3D filtering (BM3D) algorithm to address uneven illumination and complex noise issues in small-diameter, light beam, underwater imaging. Specifically, images undergo rapid illumination correction in combination with time-domain transformation. Subsequently, the proposed method employs the BM3D algorithm in conjunction with an adaptive noise-fitted model and an improved Anscombe transform for denoising. The experimental results demonstrate that the proposed method outperforms various existing image preprocessing techniques in both subjective visual assessments and objective evaluation metrics. The proposed method considerably enhances the visual quality of TG-SPAD-array-based images and is well-suited for underwater, single-photon imaging applications and for the optimized processing of high-precision, 3D depth maps.