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Paper Abstract and Keywords
Presentation 2014-07-09 15:50
high speed super-resolution based on compressed sensing
Tomohiro Yamashita, Jaehoon Yu, Yoshinori Takeuchi, Masaharu Imai (Osaka Univ.) CAS2014-16 VLD2014-25 SIP2014-37 MSS2014-16 SIS2014-16
Abstract (in Japanese) (See Japanese page) 
(in English) This paper proposes a speed-up superresolution(SR) method based on
compressed sensing, where SR is a class of techniques to generate a
high resolution image from a single or multiple low resolution
images. Because it is an ill-posed problem to generate more
information than the information of original data, conventional
methods for SR adopt machine learning or database based schemes to
estimate a plausible high resolution image. However, these types of
approaches tend to need a large size of memory and a complicated
estimation process. The SR method based on compressed sensing, used
in this paper, regards a low resolution image as the result of
a compressed form of sensing, and solves the SR problem as a
optimization problem of data reconstruction. To realize a speed-up of
the optimization process, we use the quasi-Newton method instead of
the ROMP algorithm used in the previous research. In the experimental
result using standard image database, the proposed method achieved 1
to 4 dB higher PSNR than conventional image magnification methods and
showed almost equivalent magnification performance with the method
proposed in the previous research, and realized 2 to 21 times speed-up
of processing performance.
Keyword (in Japanese) (See Japanese page) 
(in English) superresolution / compressed sensing / quasi-Newton method / / / / /  
Reference Info. IEICE Tech. Rep., vol. 114, no. 126, SIS2014-16, pp. 75-80, July 2014.
Paper # SIS2014-16 
Date of Issue 2014-07-02 (CAS, VLD, SIP, MSS, SIS) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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)
Download PDF CAS2014-16 VLD2014-25 SIP2014-37 MSS2014-16 SIS2014-16

Conference Information
Conference Date 2014-07-09 - 2014-07-11 
Place (in Japanese) (See Japanese page) 
Place (in English) Hokkaido University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) System, signal processing and related topics 
Paper Information
Registration To SIS 
Conference Code 2014-07-CAS-SIP-MSS-VLD-SIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) high speed super-resolution based on compressed sensing 
Sub Title (in English)  
Keyword(1) superresolution  
Keyword(2) compressed sensing  
Keyword(3) quasi-Newton method  
1st Author's Name Tomohiro Yamashita  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Jaehoon Yu  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Yoshinori Takeuchi  
3rd Author's Affiliation Osaka University (Osaka Univ.)
4th Author's Name Masaharu Imai  
4th Author's Affiliation Osaka University (Osaka Univ.)
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Date Time 2014-07-09 15:50:00 
Presentation Time 20 
Registration for SIS 
Paper # IEICE-CAS2014-16,IEICE-VLD2014-25,IEICE-SIP2014-37,IEICE-MSS2014-16,IEICE-SIS2014-16 
Volume (vol) IEICE-114 
Number (no) no.122(CAS), no.123(VLD), no.124(SIP), no.125(MSS), no.126(SIS) 
Page pp.75-80 
#Pages IEICE-6 
Date of Issue IEICE-CAS-2014-07-02,IEICE-VLD-2014-07-02,IEICE-SIP-2014-07-02,IEICE-MSS-2014-07-02,IEICE-SIS-2014-07-02 

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