Correspondence imaging through scattering media

Correspondence imaging (CI) realizes object reconstruction by conditionally averaging random patterns with a constant threshold which is generated from light intensities recorded by a single-pixel detector. However, object reconstruction in CI meets its challenge in complex media where the recorded light intensities fluctuate due to scaling factors existing in the optical channel. In addition, CI suffers from low quality because of conditional averaging among random patterns. In this paper, we report a varying-threshold-based CI that enables object reconstruction with high quality through complex media. To eliminate effect of dynamic scaling factors caused by complex media, varying thresholds are estimated by building an optimization model to optimize consistency between the estimations and light intensities. Then, the estimated varying thresholds can be utilized to binarize light intensities. In addition, to improve reconstruction quality, an optimization model is built by minimizing the L1 norm and total variation (TV) norm. We demonstrate the method using optical experiments. It is verified that the method can eliminate the effect of dynamic scaling factors and realize object reconstruction with high quality.

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Publication Details

Published
2025-02-05
DOI
https://doi.org/10.1117/12.3057408
Primary Topic
Medical Imaging Techniques and Applications
Type
article
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article

Correspondence imaging through scattering media

Wen Chen, Zhihan Xu
Medical Imaging Techniques and Applications
article

Correspondence imaging through scattering media

Wen Chen, Zhihan Xu
article en

Abstract

Correspondence imaging (CI) realizes object reconstruction by conditionally averaging random patterns with a constant threshold which is generated from light intensities recorded by a single-pixel detector. However, object reconstruction in CI meets its challenge in complex media where the recorded light intensities fluctuate due to scaling factors existing in the optical channel. In addition, CI suffers from low quality because of conditional averaging among random patterns. In this paper, we report a varying-threshold-based CI that enables object reconstruction with high quality through complex media. To eliminate effect of dynamic scaling factors caused by complex media, varying thresholds are estimated by building an optimization model to optimize consistency between the estimations and light intensities. Then, the estimated varying thresholds can be utilized to binarize light intensities. In addition, to improve reconstruction quality, an optimization model is built by minimizing the L1 norm and total variation (TV) norm. We demonstrate the method using optical experiments. It is verified that the method can eliminate the effect of dynamic scaling factors and realize object reconstruction with high quality.

Hong Kong Polytechnic University (HK)
Openalex Percentile: Top 97%
Medical Imaging Techniques and Applications
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