Mesh Denoising using Extended ROF Model with L1 Fidelity. (15th October 2015)

• Record Type: Journal Article
• Authors: Wu, Xiaoqun; Zheng, Jianmin; Cai, Yiyu; Fu, Chi‐Wing
• Is Part Of: Computer graphics forum. Volume 34:Number 7(2015)
• Page Start: 35
• Page End: 45
• Publication Date: 2015-10-15
• Subjects: Categories and Subject Descriptors (according to ACM CCS) -- I.3.5 [Computer Graphics]: Computational Geometry and Object Modeling—Geometric algorithms, languages, and systems; Computer graphics -- Periodicals; 006.605
• DOI: 10.1111/cgf.12743
• Languages: English
• ISSNs: 0167-7055

Abstract

Abstract: This paper presents a variational algorithm for feature‐preserved mesh denoising. At the heart of the algorithm is a novel variational model composed of three components: fidelity, regularization and fairness, which are specifically designed to have their intuitive roles. In particular, the fidelity is formulated as an L 1 data term, which makes the regularization process be less dependent on the exact value of outliers and noise. The regularization is formulated as the total absolute edge‐lengthed supplementary angle of the dihedral angle, making the model capable of reconstructing meshes with sharp features. In addition, an augmented Lagrange method is provided to efficiently solve the proposed variational model. Compared to the prior art, the new algorithm has crucial advantages in handling large scale noise, noise along random directions, and different kinds of noise, including random impulsive noise, even in the presence of sharp features. Both visual and quantitative evaluation demonstrates the superiority of the new algorithm.