Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
8947396 | Computers & Mathematics with Applications | 2018 | 19 Pages |
Abstract
Image denoising is a challenging task in the fields of image processing and computer vision. Inspired by the good performance of nonlinear fourth-order models in recovering smooth region, we proposed a fourth-order image denoising model. Using the fixed point theorem, we established the existence and uniqueness of the entropy solution. Based on the fast explicit diffusion scheme (FED), numerical experiments illustrate the effectiveness of the suggested method in image denoising. The results have been compared with three famous fourth-order models, You and Kaveh (YK) model, Lysaker, Lundervold and Tai (LLT) model and the more recent mean curvature (MC) model. The proposed model has the superiority in terms of removing noise while preserving image features.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Abdelgader Siddig, Zhichang Guo, Zhenyu Zhou, Boying Wu,