Salt and Pepper Noise Removal with Noise Detection and a Patch-Based Sparse Representation. (13th March 2014)
- Record Type:
- Journal Article
- Title:
- Salt and Pepper Noise Removal with Noise Detection and a Patch-Based Sparse Representation. (13th March 2014)
- Main Title:
- Salt and Pepper Noise Removal with Noise Detection and a Patch-Based Sparse Representation
- Authors:
- Guo, Di
Qu, Xiaobo
Du, Xiaofeng
Wu, Keshou
Chen, Xuhui - Other Names:
- Reisslein Martin Academic Editor.
- Abstract:
- Abstract : Images may be corrupted by salt and pepper impulse noise due to noisy sensors or channel transmission errors. A denoising method by detecting noise candidates and enforcing image sparsity with a patch-based sparse representation is proposed. First, noise candidates are detected and an initial guide image is obtained via an adaptive median filtering; second, a patch-based sparse representation is learnt from this guide image; third, a weighted l 1 -l 1 regularization method is proposed to penalize the noise candidates heavier than the rest of pixels. An alternating direction minimization algorithm is derived to solve the regularization model. Experiments are conducted for 30% ∼ 90% impulse noise levels, and the simulation results demonstrate that the proposed method outperforms total variation and Wavelet in terms of preserving edges and structural similarity to the noise-free images.
- Is Part Of:
- Advances in multimedia. Volume 2014(2014)
- Journal:
- Advances in multimedia
- Issue:
- Volume 2014(2014)
- Issue Display:
- Volume 2014, Issue 2014 (2014)
- Year:
- 2014
- Volume:
- 2014
- Issue:
- 2014
- Issue Sort Value:
- 2014-2014-2014-0000
- Page Start:
- Page End:
- Publication Date:
- 2014-03-13
- Subjects:
- Multimedia systems -- Periodicals
Computer networks -- Periodicals
Multimédia
Réseaux d'ordinateurs
Computer networks
Multimedia systems
Periodicals
006.7 - Journal URLs:
- https://www.hindawi.com/journals/am/ ↗
http://bibpurl.oclc.org/web/22854 ↗ - DOI:
- 10.1155/2014/682747 ↗
- Languages:
- English
- ISSNs:
- 1687-5680
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD Digital store
- Ingest File:
- 17178.xml