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| 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 |
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| 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. |
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| 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 | |
| Copyright and reproduction |
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 |
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| Conference Information | |
| Committee | CAS SIP MSS VLD SIS |
| 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 |
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| 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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| Speaker | Author-1 |
| Date Time | 2014-07-09 15:50:00 |
| Presentation Time | 20 minutes |
| Registration for | SIS |
| Paper # | CAS2014-16, VLD2014-25, SIP2014-37, MSS2014-16, SIS2014-16 |
| Volume (vol) | vol.114 |
| Number (no) | no.122(CAS), no.123(VLD), no.124(SIP), no.125(MSS), no.126(SIS) |
| Page | pp.75-80 |
| #Pages | 6 |
| Date of Issue | 2014-07-02 (CAS, VLD, SIP, MSS, SIS) |
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