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arXiv · 2309.03105

The Secrets of Non-Blind Poisson Deconvolution

Abhiram Gnanasambandam·Yash Sanghvi·Stanley H. Chan
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Abstract

Non-blind image deconvolution has been studied for several decades but most of the existing work focuses on blur instead of noise. In photon-limited conditions, however, the excessive amount of shot noise makes traditional deconvolution algorithms fail. In searching for reasons why these methods fail, we present a systematic analysis of the Poisson non-blind deconvolution algorithms reported in the literature, covering both classical and deep learning methods. We compile a list of five "secrets" highlighting the do's and don'ts when designing algorithms. Based on this analysis, we build a proof-of-concept method by combining the five secrets. We find that the new method performs on par with some of the latest methods while outperforming some older ones.

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Abhiram Gnanasambandam, Yash Sanghvi, Stanley H. Chan. 2023-09-06. The Secrets of Non-Blind Poisson Deconvolution. https://arxiv.org/abs/2309.03105

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