Computer Science

CLC number: TP751

Non-Blind Image Deblurring Method Using Shear High Order Total Variation Norm

¹ School of Mathematics and Physics, Anhui University of Technology, Maanshan 243002, Anhui, China
² Key Laboratory of Multidisciplinary Management and Control of Complex Systems of Anhui Higher Education Institutes, Anhui University of Technology, Maanshan 243002, Anhui, China

† To whom correspondence should be addressed. E-mail: zt9877@163.com

Received: 5 September 2021

Abstract

In this paper, we propose a shear high-order gradient (SHOG) operator by combining the shear operator and high-order gradient (HOG) operator. Compared with the HOG operator, the proposed SHOG operator can incorporate more directionality and detect more abundant edge information. Based on the SHOG operator, we extend the total variation (TV) norm to shear high-order total variation (SHOTV), and then propose a SHOTV deblurring model. We also study some properties of the SHOG operator, and show that the SHOG matrices are Block Circulant with Circulant Blocks (BCCB) when the shear angle is $\frac{\text{π}}{4}$. The proposed model is solved efficiently by the alternating direction method of multipliers (ADMM). Experimental results demonstrate that the proposed method outperforms some state-of-the-art non-blind deblurring methods in both objective and perceptual quality.