DMEDH: diffusion model-boosted multiplane extrapolation for digital holographic reconstruction

Digital holography can reconstruct the amplitude and phase information of the target light field. However, the reconstruction quality is largely limited by the size of the hologram. Multi-plane holograms can impose constraints for reconstruction, yet the quality of the reconstructed images continues to be restricted owing to the deficiency of effective prior information constraints. To attain high-quality image reconstruction, a diffusion model-boosted multiplane extrapolation for digital holographic reconstruction (DMEDH) algorithm is proposed. The dual-channel prior information of amplitude and phase extracted through denoising score matching is employed to constrain the physically driven dual-domain rotational iterative process. Depending on the utilization of multi-plane hologram data, the serial DMEDH and the parallel DMEDH are presented. Compared with traditional methods, simulative and experimental results demonstrate that images reconstructed using DMEDH exhibit better reconstruction quality and have higher structural similarity, peak signal-to-noise ratios, and strong generalization. The reconstructed image using DMEDH from two holograms exhibits better quality than that of traditional methods from five holograms.