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Paper Abstract and Keywords
Presentation 2026-06-04 15:35
A Proposal of Low-light Image Enhancement Method Based on Multiple Brightness Values Using Neural Architecture Search
Yuto Imamura (Kagoshima Univ.), Yoshiaki Ueda (Ryukoku Univ.), Noriaki Suetake (Yamaguchi Univ.), Satoshi Ono, Mashiho Mukaida (Kagoshima Univ.) SIS2026-5
Abstract (in Japanese) (See Japanese page) 
(in English) Low-light images captured in the environments, such as nighttime scenes, have low visibility.
General methods of image enhancement, such as gamma correction and histgram equalization,
may cause over-enhancement and saturation.
On the other hands, methods based Retinex theory and deep learning have shown high image enhancement performance.
However, these methods tend to collapse the channel balance, resulting in color shift and unnnatural color reproduction because most of conventional methods are based processing within RGB color space.
In this study, we propose a hue preserving low-light image enhancement method that applies process of enhancement only to the brightness component.
The proposed method consists of a brightness enhancement network obtained through neural architecture search, brightness fusion, and a gamut correction process that maintains the enhanced brightness values while mapping the result into the displayable RGB color space.
In the brightness enhancement network, multiple brightness values with different characteristics are jointly used to achieve both improved visibility and vividness.
Experiments demonstrate the effectiveness of proposed method through qualitative and quantitative evaluations against conventional methods and FPGA implementation of the proposed method.
Keyword (in Japanese) (See Japanese page) 
(in English) Low-light image enhancement / Retinex theory / hue preserving / brightness fusion / neural architecture search / / /  
Reference Info. IEICE Tech. Rep., vol. 126, no. 54, SIS2026-5, pp. 21-26, June 2026.
Paper # SIS2026-5 
Date of Issue 2026-05-28 (SIS) 
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 SIS2026-5

Conference Information
Committee SIS  
Conference Date 2026-06-04 - 2026-06-05 
Place (in Japanese) (See Japanese page) 
Place (in English) Iwaki Business Innovation Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Intelligent Multimedia Systems, Applied Embedded Systems, Three-Dimensional Image Technology (3DIT), etc. 
Paper Information
Registration To SIS 
Conference Code 2026-06-SIS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Proposal of Low-light Image Enhancement Method Based on Multiple Brightness Values Using Neural Architecture Search 
Sub Title (in English)  
Keyword(1) Low-light image enhancement  
Keyword(2) Retinex theory  
Keyword(3) hue preserving  
Keyword(4) brightness fusion  
Keyword(5) neural architecture search  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Yuto Imamura  
1st Author's Affiliation Kagoshima University (Kagoshima Univ.)
2nd Author's Name Yoshiaki Ueda  
2nd Author's Affiliation Ryukoku University (Ryukoku Univ.)
3rd Author's Name Noriaki Suetake  
3rd Author's Affiliation Yamaguchi University (Yamaguchi Univ.)
4th Author's Name Satoshi Ono  
4th Author's Affiliation Kagoshima University (Kagoshima Univ.)
5th Author's Name Mashiho Mukaida  
5th Author's Affiliation Kagoshima University (Kagoshima Univ.)
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Speaker Author-1 
Date Time 2026-06-04 15:35:00 
Presentation Time 20 minutes 
Registration for SIS 
Paper # SIS2026-5 
Volume (vol) vol.126 
Number (no) no.54 
Page pp.21-26 
#Pages 6 
Date of Issue 2026-05-28 (SIS) 

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