Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising

Author name not available (Why is that?)

Publication date: 1 July 2023

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.

Has companion code repository: https://github.com/kbui1993/official_aitv_poisson_denoising

This page was built for publication: Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6442261)