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arXiv · 2307.00439

Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising

Kevin Bui·Yifei Lou·Fredrick Park·Jack Xin
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Abstract

Poisson noise commonly occurs in images captured by photon-limited imaging systems such as in astronomy and medicine. As the distribution of Poisson noise depends on the pixel intensity value, noise levels vary from pixels to pixels. Hence, denoising a Poisson-corrupted image while preserving important details can be challenging. In this paper, we propose a Poisson denoising model by incorporating the weighted anisotropic-isotropic total variation (AITV) as a regularization. We then develop an alternating direction method of multipliers with a combination of a proximal operator for an efficient implementation. Lastly, numerical experiments demonstrate that our algorithm outperforms other Poisson denoising methods in terms of image quality and computational efficiency.

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Kevin Bui, Yifei Lou, Fredrick Park, Jack Xin. 2023-07-01. Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising. https://arxiv.org/abs/2307.00439

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