Introducing anisotropic tensor to high order variational model for image restoration

Duan, Jinming; Ward, Wil O.C.; Sibbett, Luke; Pan, Zhenkuan; Bai, Li

Abstract

Second order total variation (SOTV) models have advantages for image restoration over their first order counterparts including their ability to remove the staircase artefact in the restored image. However, such models tend to blur the reconstructed image when discretised for numerical solution [1–5]. To overcome this drawback, we introduce a new tensor weighted second order (TWSO) model for image restoration. Specifically, we develop a novel regulariser for the SOTV model that uses the Frobenius norm of the product of the isotropic SOTV Hessian matrix and an anisotropic tensor. We then adapt the alternating direction method of multipliers (ADMM) to solve the proposed model by breaking down the original problem into several subproblems. All the subproblems have closed-forms and can be solved efficiently. The proposed method is compared with state-of-the-art approaches such as tensor-based anisotropic diffusion, total generalised variation, and Euler's elastica. We validate the proposed TWSO model using extensive experimental results on a large number of images from the Berkeley BSDS500. We also demonstrate that our method effectively reduces both the staircase and blurring effects and outperforms existing approaches for image inpainting and denoising applications.

Citation

Duan, J., Ward, W. O., Sibbett, L., Pan, Z., & Bai, L. (in press). Introducing anisotropic tensor to high order variational model for image restoration. Digital Signal Processing, https://doi.org/10.1016/j.dsp.2017.07.001

• Journal Article Type: Article
• Acceptance Date: Jul 2, 2017
• Online Publication Date: Jul 12, 2017
• Deposit Date: Aug 3, 2017
• Publicly Available Date: Aug 3, 2017
• Journal: Digital Signal Processing
• Print ISSN: 1051-2004
• Electronic ISSN: 1051-2004
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1016/j.dsp.2017.07.001
• Public URL: https://nottingham-repository.worktribe.com/output/872416
• Publisher URL: http://www.sciencedirect.com/science/article/pii/S1051200417301434
• Contract Date: Aug 3, 2017