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| Presentation | 2020-12-18 09:15 Analysis of Scene-Adaptive Tone Mapping Methods Using Deep Learning Hirofumi Sasaki, Keita Hirai (Chiba Univ.)  IMQ2020-7 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Although high dynamic range (HDR) images can reproduce a wide range of colors and brightness, tone mapping is necessary to display them on standard monitors. Many tone mapping methods for HDR images have been proposed so far. The appearance of tone mapped images differs from method to method, but the method that provides the best appearance is not uniquely determined and is known to be dependent on the shooting scene. The goal of this research is to develop a scene dependent optimal tone mapping method, and to construct a prediction model of the optimal tone mapping method using deep learning. After that, we evaluate and analyze the prediction model with using Grad-CAM, which is a visualization method for convolution neural network’s decision making. Finally, we discuss the characteristics of various tone mapping methods and scene dependence. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | High Dynamic Range Image / Tone Mapping / Subjective Evaluation / Preference / Deep Learning / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 303, IMQ2020-7, pp. 1-4, Dec. 2020. | |
| Paper # | IMQ2020-7 | |
| Date of Issue | 2020-12-11 (IMQ) | |
| 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 | IMQ2020-7 |
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| Conference Information | |
| Committee | IMQ |
| Conference Date | 2020-12-18 - 2020-12-18 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | IMQ |
| Conference Code | 2020-12-IMQ |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Analysis of Scene-Adaptive Tone Mapping Methods Using Deep Learning |
| Sub Title (in English) | |
| Keyword(1) | High Dynamic Range Image |
| Keyword(2) | Tone Mapping |
| Keyword(3) | Subjective Evaluation |
| Keyword(4) | Preference |
| Keyword(5) | Deep Learning |
| Keyword(6) | |
| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | Hirofumi Sasaki |
| 1st Author's Affiliation | Chiba University (Chiba Univ.) |
| 2nd Author's Name | Keita Hirai |
| 2nd Author's Affiliation | Chiba University (Chiba Univ.) |
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| Speaker | Author-1 |
| Date Time | 2020-12-18 09:15:00 |
| Presentation Time | 25 minutes |
| Registration for | IMQ |
| Paper # | IMQ2020-7 |
| Volume (vol) | vol.120 |
| Number (no) | no.303 |
| Page | pp.1-4 |
| #Pages | 4 |
| Date of Issue | 2020-12-11 (IMQ) |
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