A non-local image denoising method based on TV-L1 with variable exponents

Hai Geng; Zhixin Gu; Lingyan Weng; Jian Yu

doi:10.1117/12.2680050

27 June 2023 A non-local image denoising method based on TV-L1 with variable exponents

Hai Geng, Zhixin Gu, Lingyan Weng, Jian Yu

Proceedings Volume 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022); 1270525 (2023) https://doi.org/10.1117/12.2680050
Event: Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 2022, Nanjing, China

Abstract

Among various image denoising methods, the total variation (TV) has offered considerable performance. However, it is prone to the staircasing effect. To alleviate this problem, we propose a novel TV-based denoising method that utilizes variable exponents as the regularization constraints and L1-norm as the fidelity term. To further improve the robustness of our method, we develop it under a non-local framework to avoid overlooking the global information of the image. Extensive experiments on real-world images have validated the effectiveness of the proposed method.

Citation Download Citation

Hai Geng, Zhixin Gu, Lingyan Weng, and Jian Yu "A non-local image denoising method based on TV-L1 with variable exponents", Proc. SPIE 12705, Fourteenth International Conference on Graphics and Image Processing (ICGIP 2022), 1270525 (27 June 2023); https://doi.org/10.1117/12.2680050

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available