| Paper Abstract and Keywords |
| Presentation |
2026-02-19 16:30
Image Denoising Method Based on DnCNN with Low Training Cost Deyu Gong, Mitsuhiko Meguro (Nihon Univ.) ITS2025-59 IE2025-74 |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Image denoising has continuously attracted much attention as an important research topic. To improve the restoration performance of degraded images, DnCNN based on convolutional neural networks (CNNs) has been proposed and has demonstrated high denoising capability. However, DnCNN requires a long training time, and a large batch size is necessary to achieve high-accuracy image restoration. In this study, we focus on the Residual Excitation structure and the Attention mechanism that have been proposed in EDCNN and CBAM-DnCNN, respectively. By integrating these mechanisms, we propose an improved DnCNN model. The proposed method enables faster training with a smaller batch size compared with the conventional DnCNN, while maintaining high denoising performance. Its effectiveness is demonstrated through various application examples. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Image Denoising / DnCNN / Attention / Residual Excitation / Deep learning / / / |
| Reference Info. |
IEICE Tech. Rep., vol. 125, no. 356, IE2025-74, pp. 113-118, Feb. 2026. |
| Paper # |
IE2025-74 |
| Date of Issue |
2026-02-12 (ITS, IE) |
| ISSN |
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 |
ITS2025-59 IE2025-74 |
| Conference Information |
| Committee |
IE ITS ITE-MMS ITE-ME ITE-AIT ITE-SIP |
| Conference Date |
2026-02-19 - 2026-02-20 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
|
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
IE |
| Conference Code |
2026-02-IE-ITS-MMS-ME-AIT-SIP |
| Language |
Japanese |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Image Denoising Method Based on DnCNN with Low Training Cost |
| Sub Title (in English) |
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| Keyword(1) |
Image Denoising |
| Keyword(2) |
DnCNN |
| Keyword(3) |
Attention |
| Keyword(4) |
Residual Excitation |
| Keyword(5) |
Deep learning |
| Keyword(6) |
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| Keyword(7) |
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| Keyword(8) |
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| 1st Author's Name |
Deyu Gong |
| 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 |
2026-02-19 16:30:00 |
| Presentation Time |
15 minutes |
| Registration for |
IE |
| Paper # |
ITS2025-59, IE2025-74 |
| Volume (vol) |
vol.125 |
| Number (no) |
no.355(ITS), no.356(IE) |
| Page |
pp.113-118 |
| #Pages |
6 |
| Date of Issue |
2026-02-12 (ITS, IE) |