NDLI: Image denoising via bidirectional low rank representation with cluster adaptive dictionary

Content Provider	IET Digital Library
Author	Li, Xiaoping Wang, Weiwei Feng, Xiangchu Liu, Xiaoyan Luo, Liang
Abstract	In this study, the authors propose a new image representation model that fully exploits the similarity inherent in natural images. The idea is based on an observation of similar patches. For a clean image, when a cluster of similar patches are collected to form the similar patch matrix (SPM), there exists high correlation among columns/rows of the SPM. This implies that, when the column/row vectors are linearly expressed by a dictionary, their coefficients of columns/rows should have high correlation, which leads to the coefficient matrixes of column/row representation are low-ranked. This observation inspires them to propose a novel image denoising model named bidirectional low rank representation (BiLRR) with cluster adaptive dictionary. Specifically, they use low rank penalties simultaneously on the coefficient matrixes of column and row representations to recover the correlation structure of the SPM. Meanwhile, a cluster adaptive dictionary is learned to represent each SPM so as to well preserve the fine structure of image. By applying variable splitting and penalty technique, they present an efficient alternative minimisation algorithm to solve the proposed BiLRR model. Experimental results indicate the authors’ method achieves a competitive denoising performance in comparison with state-of-the-art algorithms in terms of subjective and objective qualities.
Starting Page	952
Ending Page	961
Page Count	10
ISSN	17519659
Volume Number	10
e-ISSN	17519667
Issue Number	Issue 12, Dec (2016)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/10/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2016.0257
Journal	IET Image Processing
Publisher Date	2016-07-12
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Bidirectional Low Rank Representation BiLRR Model Clean Image Cluster Adaptive Dictionary Coefficient Matrices Column Representation Computer Vision And Image Processing Technique Correlation Method Correlation Structure Recovery Fine Structure Preservation Image Denoising Image Denoising Model Image Representation Image Representation Model Low Rank Penalties Matrix Algebra Minimisation Minimisation Algorithm Natural Image Self-similarity Optical, Image And Video Signal Processing Optimisation Technique Pattern Clustering Performance Improvement Row Representation Similar Patch Matrix SPM
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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