Optimizing shape from polarization using Fourier light field microscopy depth

Shape from Polarization (SFP) is a three-dimensional (3D) reconstruction technique that leverages the polarization properties of light to derive surface morphology. Its capabilities in non-destructive inspection make it particularly valuable in microscopy applications. However, SFP encounters challenges such as normal azimuth ambiguity and depth uncertainty. To address these issues, this paper proposes an optimized scheme that utilizes depth information from Fourier light field microscopy (FLFM) to assist in the reconstruction of SFP. We have developed a dual-optical-path FLFM-polarization microscope system that concurrently captures high-resolution polarization images and Fourier light field images containing spatial-angular information. By employing depth information derived from FLFM, we corrected ambiguous azimuth angles and optimized the SFP results through a variational reconstruction model incorporating depth and projection constraints. Quantitative assessments using mean absolute error (MAE) and structural similarity metrics (SSIM) on FLFM-assisted SFP reconstructions of polystyrene microspheres, validated against atomic force microscopy 3D measurements, confirmed significant enhancements in reconstruction accuracy.