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A one-bit quantization approach for low-dose Poisson phase retrieval.
In: (2024 International Workshop on the Theory of Computational Sensing and its Applications to Radar, Multimodal Sensing and Imaging, CoSeRa 2024). 2024. 42-46 (2024 International Workshop on the Theory of Computational Sensing and its Applications to Radar, Multimodal Sensing and Imaging, CoSeRa 2024)
Imaging quality for biological tissue is commonly affected by damages of the specimen caused by illumination particles. To mitigate this issue, often very low doses of illumination have to be used in the experiment. Consequently, the resulting inverse problem is subject to highly noisy data. In this note, we address this issue for the case of diffraction imaging by studying the problem of phase retrieval with low-count Poisson data. Our key idea is to exploit the close connection between the Poisson measurement model and the one-bit quantization problem. We propose a reconstruction method based on algorithmic approaches to that problem and compare the performance of this method with state-of-the-art algorithms for noisy phase retrieval, observing superior performance in a number of relevant examples.
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Publication type
Article: Conference contribution
Keywords
Low-dose Imaging ; One-bit Quantization ; Phase Retrieval ; Poisson Noise
ISSN (print) / ISBN
[9798350365504]
Conference Title
2024 International Workshop on the Theory of Computational Sensing and its Applications to Radar, Multimodal Sensing and Imaging, CoSeRa 2024
Quellenangaben
Pages: 42-46
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Institute(s)
Institute of Biological and Medical Imaging (IBMI)