Scattered light field separation and high-quality imaging based on low-rank sparse matrix decomposition

Kang Liu; Pinghe Wang

doi:10.1117/12.3046629

5 December 2024 Scattered light field separation and high-quality imaging based on low-rank sparse matrix decomposition

Kang Liu, Pinghe Wang

Author Affiliations +

Proceedings Volume 13418, Fifteenth International Conference on Information Optics and Photonics (CIOP 2024); 134180S (2024) https://doi.org/10.1117/12.3046629
Event: 15th International Conference on Information Optics and Photonics (CIOP2024), 2024, Xi’an, China

Abstract

The absorption and scattering properties of light in biological tissues reflect their key characteristics. However, strong background light often obscures these properties. Currently, contrast enhancement in imaging primarily focuses on noise reduction from an image processing perspective rather than considering the properties of the light field itself. This approach has limitations in preserving imaging details and information, particularly under strong background light conditions, leading to information loss. This paper introduces an imaging technique based on the Low-rank Sparse Matrix Decomposition (LSMD) to achieve high-quality imaging of biological tissues. Experiments in Gaussian and ring-shaped light fields validate that the low-rank component of the light field represents background light, while the sparse component indicates the scattering and absorption properties of the target. This technique effectively highlights microscopic details and scattering/absorption characteristics. Compared to traditional image-based filtering methods, this light field-based technique significantly improves the extraction of absorption and scattering information. It has the potential to enhance tissue visualization in medical diagnostics and research.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

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Kang Liu and Pinghe Wang "Scattered light field separation and high-quality imaging based on low-rank sparse matrix decomposition", Proc. SPIE 13418, Fifteenth International Conference on Information Optics and Photonics (CIOP 2024), 134180S (5 December 2024); https://doi.org/10.1117/12.3046629

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KEYWORDS

Biological imaging

Matrices

Tissues

Light scattering

Light absorption

Image filtering

Tunable filters

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