NDLI: Low complexity intra MB encoding in AVC/H.264

Content Provider	IEEE Xplore Digital Library
Author	Jillani, R. Kalva, H.
Copyright Year	1975
Abstract	In this paper we introduce and evaluate a novel machine learning based approach to reduce the complexity of Intra macroblock (MB) coding. The proposed approach is based on the hypothesis that MB coding mode decisions in H.264/AVC video have a correlation with the intensities of adjacent MBs and sub-MBs. This paper also discusses and analyzes different approaches of using machine learning in Intra prediction. We discuss, amongst other features, slices, Intra prediction scheme for H.264 and data mining. We use data mining algorithms to develop decision trees for H.264 coding mode decisions. The proposed approach reduces the H.264/AVC MB mode computation process into a decision tree lookup with very low complexity. The proposed algorithm is implemented in reference software by modifying the source code and is compared with the JM reference software for H.264/AVC.
Sponsorship	IEEE Consumer Electronics Society
File Size	662044
File Format	PDF
ISSN	00983063
Volume Number	55
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-02-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Encoding Automatic voltage control Video coding Machine learning Data mining IEC standards ISO standards Machine learning algorithms Decision trees MPEG 4 Standard machine learning H.264/AVC intra prediction data mining
Content Type	Text
Resource Type	Article
Subject	Electrical and Electronic Engineering Media Technology

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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
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