arXiv Open Access 2023

Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising

Kevin Bui Yifei Lou Fredrick Park Jack Xin

Lihat Sumber

Abstrak

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.

Topik & Kata Kunci

eess.IV cs.CV math.NA

Penulis (4)

Kevin Bui

Yifei Lou

Fredrick Park

Jack Xin

Format Sitasi

APA MLA BibTeX

Bui, K., Lou, Y., Park, F., Xin, J. (2023). Weighted Anisotropic-Isotropic Total Variation for Poisson Denoising. https://arxiv.org/abs/2307.00439

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Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓