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Paper Abstract and Keywords
Presentation 2012-03-08 12:20
Distributed Video Coding by applying Super Resolution with Learning-Based Kernel Regression
Ryotaro Nakamura, Shinobu Kudo (Keio Univ.), Takayuki Nakachi (NTT), Nozomu Hamada (Keio Univ.) CAS2011-111 SIP2011-131 CS2011-103
Abstract (in Japanese) (See Japanese page) 
(in English) Distributed video coding (DVC) is a novel and interesting video coding scheme which utilizes inter-frame prediction at decoder. However, the coding efficiency of DVC is inferior as compared to the existing coding systems such as H.264/AVC etc. The coding efficiency of DVC is significantly affected by the prediction accuracy at generating side information and the data amount of the key-frames. This study tries to improve the coding efficiency of DVC by applying super resolution technique. The bit rate for key-frame coding is reduced by employing down-sampling at the encoder. In addition, the side information is generated by applying motion-compensation to the key frames with low resolution, then image interpolation employing kernel regression algorithm is applied. This process may reduce the amount of error correction. Experiments applied to several standard video images show the coding efficiency improvement by the proposed method at medium- and low-bit-rates.
Keyword (in Japanese) (See Japanese page) 
(in English) Distributed Video Coding / Super Resokution / Kernel Regression / Video Coding / k-means Clustering / / /  
Reference Info. IEICE Tech. Rep., vol. 111, no. 466, SIP2011-131, pp. 25-30, March 2012.
Paper # SIP2011-131 
Date of Issue 2012-03-01 (CAS, SIP, CS) 
ISSN Print edition: ISSN 0913-5685    Online edition: ISSN 2432-6380
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All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee CAS CS SIP  
Conference Date 2012-03-08 - 2012-03-09 
Place (in Japanese) (See Japanese page) 
Place (in English) The University of Niigata 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Network Processor, Signal Processing for communication, and Wireless LAN/PAN, etc. 
Paper Information
Registration To SIP 
Conference Code 2012-03-CAS-CS-SIP 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Distributed Video Coding by applying Super Resolution with Learning-Based Kernel Regression 
Sub Title (in English)  
Keyword(1) Distributed Video Coding  
Keyword(2) Super Resokution  
Keyword(3) Kernel Regression  
Keyword(4) Video Coding  
Keyword(5) k-means Clustering  
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1st Author's Name Ryotaro Nakamura  
1st Author's Affiliation Keio University (Keio Univ.)
2nd Author's Name Shinobu Kudo  
2nd Author's Affiliation Keio University (Keio Univ.)
3rd Author's Name Takayuki Nakachi  
3rd Author's Affiliation NIPPON TELEGRAPH AND TELEPHONE CORPORATION (NTT)
4th Author's Name Nozomu Hamada  
4th Author's Affiliation Keio University (Keio Univ.)
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Speaker Author-1 
Date Time 2012-03-08 12:20:00 
Presentation Time 25 minutes 
Registration for SIP 
Paper # CAS2011-111, SIP2011-131, CS2011-103 
Volume (vol) vol.111 
Number (no) no.465(CAS), no.466(SIP), no.467(CS) 
Page pp.25-30 
#Pages
Date of Issue 2012-03-01 (CAS, SIP, CS) 


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