Rethinking Low-Light Image Enhancement: A Log-Domain Intensity--Chromaticity Decoupling Perspective

Fuente: arXiv
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Hauptverfasser: Bai, Guangrui, Mei, Yifan, Deng, Yahui, Chen, Yuhan, Qiu, Yuze, Liu, Wenhai, Dong, Erbao
Format: Preprint
Veröffentlicht: 2026
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author Bai, Guangrui
Mei, Yifan
Deng, Yahui
Chen, Yuhan
Qiu, Yuze
Liu, Wenhai
Dong, Erbao
author_facet Bai, Guangrui
Mei, Yifan
Deng, Yahui
Chen, Yuhan
Qiu, Yuze
Liu, Wenhai
Dong, Erbao
contents Explicit reconstruction constraints derived from the decoupled representation are further imposed to suppress abnormal channel amplification and chromatic noise. Experiments on LOLv2-Real, MIT-Adobe FiveK, and LSRW show that the proposed method achieves competitive or superior quantitative and visual performance, reaching 29.71 dB PSNR and 0.89 SSIM on LOLv2-Real. DarkFace experiments further indicate improved downstream face detection under low-light conditions. Code and pretrained models are available at: https://github.com/mubaisam/ICD.
format Preprint
id arxiv_https___arxiv_org_abs_2605_02627
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Rethinking Low-Light Image Enhancement: A Log-Domain Intensity--Chromaticity Decoupling Perspective
Bai, Guangrui
Mei, Yifan
Deng, Yahui
Chen, Yuhan
Qiu, Yuze
Liu, Wenhai
Dong, Erbao
Computer Vision and Pattern Recognition
Explicit reconstruction constraints derived from the decoupled representation are further imposed to suppress abnormal channel amplification and chromatic noise. Experiments on LOLv2-Real, MIT-Adobe FiveK, and LSRW show that the proposed method achieves competitive or superior quantitative and visual performance, reaching 29.71 dB PSNR and 0.89 SSIM on LOLv2-Real. DarkFace experiments further indicate improved downstream face detection under low-light conditions. Code and pretrained models are available at: https://github.com/mubaisam/ICD.
title Rethinking Low-Light Image Enhancement: A Log-Domain Intensity--Chromaticity Decoupling Perspective
topic Computer Vision and Pattern Recognition
url https://arxiv.org/abs/2605.02627