Polarization as Texture: Microscale 3D Shape from Polarized Light Focus

Defocus is a crucial cue for image-based microscale depth estimation, yet its measurement depends on spatial appearance changes, such as texture. We show that passively observed polarization is responsive to small irregularities of the surface visible in the microscopic world and can be leveraged for focus measure as a strong texture. Our key idea is to leverage texture from polarization for blur analysis and accurately estimate the focus level of microscopic polarization images. We further utilize normal cues from polarization to create a prior distribution of the focus level between neighboring pixels. We then interpolatively propagate the focus level of discrete image slices at different focus depths while denoising. We implement our method with a single polarization camera with a microscope and recover the per-pixel depth from the multi-focus images. The reconstructed results demonstrate the effectiveness of our method for various microscale objects regardless of the surface texture.

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Publication Details

Published
2025-02-26
DOI
https://doi.org/10.1109/wacv61041.2025.00060
Primary Topic
Optical measurement and interference techniques
Type
article
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article

Polarization as Texture: Microscale 3D Shape from Polarized Light Focus

Ryo Kawahara, Ryosuke MATSUMOTO, Takahiro Okabe
Optical measurement and interference techniques
article

Polarization as Texture: Microscale 3D Shape from Polarized Light Focus

Ryo Kawahara, Ryosuke MATSUMOTO, Takahiro Okabe
article en

Abstract

Defocus is a crucial cue for image-based microscale depth estimation, yet its measurement depends on spatial appearance changes, such as texture. We show that passively observed polarization is responsive to small irregularities of the surface visible in the microscopic world and can be leveraged for focus measure as a strong texture. Our key idea is to leverage texture from polarization for blur analysis and accurately estimate the focus level of microscopic polarization images. We further utilize normal cues from polarization to create a prior distribution of the focus level between neighboring pixels. We then interpolatively propagate the focus level of discrete image slices at different focus depths while denoising. We implement our method with a single polarization camera with a microscope and recover the per-pixel depth from the multi-focus images. The reconstructed results demonstrate the effectiveness of our method for various microscale objects regardless of the surface texture.

Okayama University (JP), Kyushu Institute of Technology (JP), Kyoto University (JP), Kyushu Art Institute of Technology (JP)
Openalex Percentile: Top 94%
Optical measurement and interference techniques
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