The Secrets of Non-Blind Poisson Deconvolution

Autor:	Gnanasambandam, Abhiram, Sanghvi, Yash, Chan, Stanley H.
Rok vydání:	2023
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing
Druh dokumentu:	Working Paper
Popis:	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. Comment: Under submission at Transactions on Computational Imaging
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2309.03105 Zobrazit plný text záznamu View this record from Arxiv