Robustness of low-light lensless imaging with camera noise

In this paper, we evaluate the noise sensitivity of mask based lensless imaging by analysing how much information is lost due to camera noise in low-light conditions. A noise model based on a lensless imaging system under lowlight conditions is presented for noise analysis in lensless imaging. The structure utilises the noise-free point spread function (PSF) of a diffuser-based lensless system to generate a noisy PSF from a camera in a real-world low-light environment. We then use a statistical approach to observe how the amount of mutual information between the noiseless and the noisy PSF’s is affected with the enhancement of camera noise. We performed the same simulation for comparison with lens-based imaging. We demonstrate that the proposed model and the mask based lensless imaging system exhibits better robustness than the lens-based imaging system in low-light environments.

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Publication Details

Published
2024-11-23
DOI
https://doi.org/10.1117/12.3037116
Primary Topic
Optical Coherence Tomography Applications
Type
article
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Robustness of low-light lensless imaging with camera noise

Wensi Zhang, Tianjiao Zeng, Xu Zhan, Xiaoling Zhang et al.
Optical Coherence Tomography Applications
article

Robustness of low-light lensless imaging with camera noise

Wensi Zhang, Tianjiao Zeng, Xu Zhan, Xiaoling Zhang, Yuwei Liu
article en

Abstract

In this paper, we evaluate the noise sensitivity of mask based lensless imaging by analysing how much information is lost due to camera noise in low-light conditions. A noise model based on a lensless imaging system under lowlight conditions is presented for noise analysis in lensless imaging. The structure utilises the noise-free point spread function (PSF) of a diffuser-based lensless system to generate a noisy PSF from a camera in a real-world low-light environment. We then use a statistical approach to observe how the amount of mutual information between the noiseless and the noisy PSF’s is affected with the enhancement of camera noise. We performed the same simulation for comparison with lens-based imaging. We demonstrate that the proposed model and the mask based lensless imaging system exhibits better robustness than the lens-based imaging system in low-light environments.

University of Electronic Science and Technology of China (CN)
Affordable and clean energy
Openalex Percentile: Top 81%
Optical Coherence Tomography Applications
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