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| Presentation | 2018-12-07 11:05 Chromatic Aberration Correction of Color Images Using Deep Neural Network for Each Channel Processing Naoto Nagashima, Mitsuhiko Meguro (Nihon Univ.)  SIS2018-33 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In this paper, we propose a new correcting method of chromatic aberration occurring in color images using Deep Learning. In this proposed method, the existing Deep Learning for denoising (well known as DnCNN) is used for chromatic aberration correction purpose. In a lens optical system for imaging, the wavelength of $G$ is designed to be in focus. Therefore, light $R$ with longer wavelength than $G$ and light $B$ with shorter wavelength are out of focus and may cause chromatic aberration. We propose a method to remove the deterioration of chromatic aberration of $R$ channel and $B$ channel by using the $G$ channel without chromatic aberration. DnCNN needs to be trained with both chromatic aberration images and original images not including these aberrations. In the case of learning DnCNN for restoration of $R$, it is better to perform correction with CNN learned using only learning data of $R$ and $G$. Moreover, for restoration $B$ channel, it is better using $B$ and $G$ data only than using all $RGB$ data. By separating the two DnCNN networks to be trained for the $R$ or $B$ channels, an accuracy and an efficiency of DnCNN can be improved. Through experimental results, we show the effectiveness of our proposed method. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | chromatic aberration / Deep Learning / color channel / color image processing / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 346, SIS2018-33, pp. 61-66, Dec. 2018. | |
| Paper # | SIS2018-33 | |
| Date of Issue | 2018-11-29 (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 | SIS2018-33 |
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| Conference Information | |
| Committee | SIS |
| Conference Date | 2018-12-06 - 2018-12-07 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hagi Civic Center |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Smart Personal Systems, etc. |
| Paper Information | |
| Registration To | SIS |
| Conference Code | 2018-12-SIS |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Chromatic Aberration Correction of Color Images Using Deep Neural Network for Each Channel Processing |
| Sub Title (in English) | |
| Keyword(1) | chromatic aberration |
| Keyword(2) | Deep Learning |
| Keyword(3) | color channel |
| Keyword(4) | color image processing |
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| 1st Author's Name | Naoto Nagashima |
| 1st Author's Affiliation | Nihon University (Nihon Univ.) |
| 2nd Author's Name | Mitsuhiko Meguro |
| 2nd Author's Affiliation | Nihon University (Nihon Univ.) |
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| Speaker | Author-1 |
| Date Time | 2018-12-07 11:05:00 |
| Presentation Time | 20 minutes |
| Registration for | SIS |
| Paper # | SIS2018-33 |
| Volume (vol) | vol.118 |
| Number (no) | no.346 |
| Page | pp.61-66 |
| #Pages | 6 |
| Date of Issue | 2018-11-29 (SIS) |
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