NDLI: Image Blocking Artifacts Reduction via Patch Clustering and Low-Rank Minimization

Content Provider	IEEE Xplore Digital Library
Author	Jie Ren Jiaying Liu Mading Li Wei Bai Zongming Guo
Copyright Year	2013
Description	Author affiliation: Instn. of Comput. Sci. & Technol., Peking Univ., Beijing, China (Jie Ren; Jiaying Liu; Mading Li; Wei Bai; Zongming Guo)
Abstract	Summary form only given. Block-based Discrete Cosine Transform (BDCT) has been widely used in image and video compression due to its energy compacting property and relative ease of implementation. However, BDCT has a major drawback, which is usually referred to as blocking artifacts. Blocking artifacts appear as grid noise along the block boundaries because each block is transformed and quantized independently. Image deblocking techniques can reduce these distortions and alleviate the conflict between bit rate reduction and visual quality preservation. Many state-of-the-art image deblocking algorithms treated the blocking artifacts reduction of the compressed image as an inverse restoration problem. Natural image prior models are well utilized into the blocking artifacts reduction processing, such as the local sparsity prior model and non-local similarity property of natural images. These two local and non-local models characterize the image prior information in two complementary perspectives. Therefore, it is necessary to combine these two models in a unified framework. In this paper, we propose a novel method to reduce the blocking artifacts of blockcoded images via patch clustering and low-rank minimization, which simultaneously exploits the local and non-local sparse representations in a unified framework. First, the whole compressed image are divided into small patches. For each patch, we perform patch clustering to collect similar patches into a group. Then the whole group are simultaneously reconstructed by a low-rank minimization approach. Singular value thresholding (SVT) algorithm is employed to solve the low-rank minimization problem. To further improve the performance of the proposed algorithm, we adopt an iterative procedure to utilize the newly output data in each iteration and update the noise and signal variance adaptively. Experimental results show that the proposed method achieves higher PSNR and SSIM than the state-of-the-art methods. Comparing to the state-of-theart algorithms and, the proposed algorithm achieves about 0.37dB and 0.11dB improvement on average. For visual quality assessment, the deblocking images produced by the proposed algorithm reveal much more sharp edge structures and richer textures.
Sponsorship	Univ. Arizona
Starting Page	516
Ending Page	516
File Size	476594
Page Count	1
File Format	PDF
ISBN	9781467360371
ISSN	10680314
e-ISBN	9780769549651
DOI	10.1109/DCC.2013.95
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-03-20
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Minimization Image coding Contracts Noise Visualization Clustering algorithms Data compression low-rank minimization image deblocking patch clustering
Content Type	Text
Resource Type	Article
Subject	Computer Networks and Communications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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