Comparative evaluation of denoising methods for off-axis digital holograms under realistic mixed-noise conditions

Abstract

Off-axis holographic microscopy enables single-shot quantitative phase imaging, but its sensitivity is limited by mixed noise that degrades fringe visibility and biases phase recovery. We compare classical filters (Wiener/median/NLM/BM3D and variance-stabilized variants), a supervised Swin transformer, and a diffusion denoiser trained on synthetic data, using 100,000 physics-based holograms with realistic blur, speckle, shot, and read noise. On a 10,000-hologram test set, the best pipeline (diffusion followed by BM3D) achieves 36.86 dB/0.9964 intensity PSNR/SSIM and 46.48 dB/0.9772 phase PSNR/SSIM, reducing RMSE by 88.5% in intensity and 52.8% in phase, with similar improvements on experimental bead and cell holograms.