A Modified Iterative Alternating Direction Minimization Algorithm for Impulse Noise Removal in Images

Di Guo, Xiaobo Qu, Meng Wu and Keshou Wu

Journal of Applied Mathematics, 2014, vol. 2014, issue 1

Abstract: Images are often corrupted by impulse noise. In this paper, an alternating direction minimization with continuation algorithm is modified and iteratively used to remove the impulse noise in images by exploring its self‐similarity. A patch‐based nonlocal operator and sparse representation are married in the l1‐l1 optimization model to be solved. Simulation results demonstrate that the proposed algorithm outperforms typical denoising methods in terms of preserving edges and textures for both salt‐and‐pepper noise and random‐valued impulse noise. It can be also applied to suppress impulse noise‐like artifacts in real mural images.

Date: 2014
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1155/2014/595782

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jnljam:v:2014:y:2014:i:1:n:595782

Access Statistics for this article

More articles in Journal of Applied Mathematics from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().