ITRE: Low-light image enhancement based on illumination transmission ratio estimation

IF 4.4 2区 化学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Yu Wang , Yihong Wang , Tong Liu , Jinyu Li , Xiubao Sui , Qian Chen
{"title":"ITRE: Low-light image enhancement based on illumination transmission ratio estimation","authors":"Yu Wang ,&nbsp;Yihong Wang ,&nbsp;Tong Liu ,&nbsp;Jinyu Li ,&nbsp;Xiubao Sui ,&nbsp;Qian Chen","doi":"10.1016/j.knosys.2024.112427","DOIUrl":null,"url":null,"abstract":"<div><p>Noise, artifacts, and over-exposure are substantial challenges in the field of low-light image enhancement. Existing methods often struggle to address these issues simultaneously. In this paper, we propose a method that is based on Illumination Transmission Ratio Estimation (ITRE) to handle the challenges at the same time. Specifically, we assume that there must exist a pixel which is least disturbed by low light for pixels of each color cluster. First, we cluster the pixels on the RGB color space to find the Illumination Transmission Ratio (ITR) matrix of the whole image, which determines that noise is not over-amplified easily. Next, we consider the ITR of the image as the initial illumination transmission map to construct a base model for refining transmission map, which prevents artifacts. In addition, we design an over-exposure module that captures the fundamental characteristics of pixel over-exposure and seamlessly integrates it into the base model. Finally, there is a possibility of weak enhancement when the interclass distance of pixels with the same color is too small. To counteract this, we design an Robust-Guard (RG) module that safeguards the robustness of the image enhancement process. Extensive experiments demonstrate the superiority of the proposed method over state-of-the-art methods in terms of visual quality and quantitative metrics. Our code is available at <span><span>https://github.com/wangyuro/ITRE</span><svg><path></path></svg></span>.</p></div>","PeriodicalId":7,"journal":{"name":"ACS Applied Polymer Materials","volume":null,"pages":null},"PeriodicalIF":4.4000,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Polymer Materials","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S095070512401061X","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

Noise, artifacts, and over-exposure are substantial challenges in the field of low-light image enhancement. Existing methods often struggle to address these issues simultaneously. In this paper, we propose a method that is based on Illumination Transmission Ratio Estimation (ITRE) to handle the challenges at the same time. Specifically, we assume that there must exist a pixel which is least disturbed by low light for pixels of each color cluster. First, we cluster the pixels on the RGB color space to find the Illumination Transmission Ratio (ITR) matrix of the whole image, which determines that noise is not over-amplified easily. Next, we consider the ITR of the image as the initial illumination transmission map to construct a base model for refining transmission map, which prevents artifacts. In addition, we design an over-exposure module that captures the fundamental characteristics of pixel over-exposure and seamlessly integrates it into the base model. Finally, there is a possibility of weak enhancement when the interclass distance of pixels with the same color is too small. To counteract this, we design an Robust-Guard (RG) module that safeguards the robustness of the image enhancement process. Extensive experiments demonstrate the superiority of the proposed method over state-of-the-art methods in terms of visual quality and quantitative metrics. Our code is available at https://github.com/wangyuro/ITRE.

ITRE: 基于照明透射比估算的低照度图像增强技术
在弱光图像增强领域,噪点、伪像和过度曝光是巨大的挑战。现有的方法往往难以同时解决这些问题。在本文中,我们提出了一种基于光照传输比估计(ITRE)的方法,以同时应对这些挑战。具体来说,我们假定每个颜色群组的像素中一定存在一个受弱光干扰最小的像素。首先,我们在 RGB 色彩空间上对像素进行聚类,找出整幅图像的照明透射比矩阵(ITR),从而确定噪声不易被过度放大。接下来,我们将图像的光照透射比矩阵视为初始光照透射图,从而构建一个基础模型来细化透射图,以防止出现伪影。此外,我们还设计了一个过曝模块,可以捕捉像素过曝的基本特征,并将其无缝集成到基础模型中。最后,当同色系像素的类间距离过小时,可能会出现弱增强。为了解决这个问题,我们设计了一个鲁棒守护(RG)模块,以确保图像增强过程的鲁棒性。广泛的实验证明,在视觉质量和定量指标方面,所提出的方法优于最先进的方法。我们的代码见 https://github.com/wangyuro/ITRE。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
7.20
自引率
6.00%
发文量
810
期刊介绍: ACS Applied Polymer Materials is an interdisciplinary journal publishing original research covering all aspects of engineering, chemistry, physics, and biology relevant to applications of polymers. The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates fundamental knowledge in the areas of materials, engineering, physics, bioscience, polymer science and chemistry into important polymer applications. The journal is specifically interested in work that addresses relationships among structure, processing, morphology, chemistry, properties, and function as well as work that provide insights into mechanisms critical to the performance of the polymer for applications.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信