Two-Step Approach for the Restoration of Images Corrupted by Multiplicative Noise
| Autor: | De Yong Lu, Yu-Mei Huang, Tieyong Zeng |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Deblurring
business.industry Applied Mathematics ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Regular polygon Total variation denoising Multiplicative noise Term (time) Computational Mathematics Variational method Computer Science::Computer Vision and Pattern Recognition Convergence (routing) Computer vision Artificial intelligence business Algorithm Image restoration Mathematics |
| Zdroj: | SIAM Journal on Scientific Computing. 35:A2856-A2873 |
| ISSN: | 1095-7197 1064-8275 |
| Popis: | The restoration of images corrupted by blurring and multiplicative noise is a challenging problem in applied mathematics that has attracted much attention in recent years. In this article, we propose a two-step approach to solve the problem of restoring images degraded by multiplicative noise and blurring, where the multiplicative noise is first reduced by nonlocal filters and then a convex variational model is adopted to obtain the final restored images. The variational model of the second step is composed of an $L_1$-$L_2$ data-fidelity term and a total variation regularization term. The alternating direction method (ADM) is utilized to solve this variational problem, and we also prove that the ADM algorithm converges at least linearly. Experimental results show that the proposed two-step approach performs better than the existing methods for restoring images with multiplicative noise and blurring, both in the quality of the restored images and the convergence speed of the algorithms. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|