基于高阶变分模型的低照度图像识别

IF 1.8 3区 工程技术 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC Circuits, Systems and Signal Processing Pub Date : 2024-08-14 DOI:10.1007/s00034-024-02762-7
Yanan Gu, Yiming Gao, Dong Wang, Chunyang Wang, Bibo Lu
{"title":"基于高阶变分模型的低照度图像识别","authors":"Yanan Gu, Yiming Gao, Dong Wang, Chunyang Wang, Bibo Lu","doi":"10.1007/s00034-024-02762-7","DOIUrl":null,"url":null,"abstract":"<p>The existing rain streaks removal methods provide better deraining results, but it cannot be implemented on the low-light images due to the poor visual quality. To solve this problem, this paper presents a novel rain streaks removal approach using m fold infimal convolution of oscillating TGV(<span>\\(ICTGV^{osci}\\)</span>) regularization and Retinex theory for low-light images. Experiments on a number of challenging low-light rainy images are presented to demonstrate the efficiency and the flexibility of the proposed approaches in comparison with state-of-the-art methods.</p>","PeriodicalId":10227,"journal":{"name":"Circuits, Systems and Signal Processing","volume":"28 1","pages":""},"PeriodicalIF":1.8000,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Low-Light Image Deraining Based on Higher Order Variational Model\",\"authors\":\"Yanan Gu, Yiming Gao, Dong Wang, Chunyang Wang, Bibo Lu\",\"doi\":\"10.1007/s00034-024-02762-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>The existing rain streaks removal methods provide better deraining results, but it cannot be implemented on the low-light images due to the poor visual quality. To solve this problem, this paper presents a novel rain streaks removal approach using m fold infimal convolution of oscillating TGV(<span>\\\\(ICTGV^{osci}\\\\)</span>) regularization and Retinex theory for low-light images. Experiments on a number of challenging low-light rainy images are presented to demonstrate the efficiency and the flexibility of the proposed approaches in comparison with state-of-the-art methods.</p>\",\"PeriodicalId\":10227,\"journal\":{\"name\":\"Circuits, Systems and Signal Processing\",\"volume\":\"28 1\",\"pages\":\"\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2024-08-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Circuits, Systems and Signal Processing\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s00034-024-02762-7\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Circuits, Systems and Signal Processing","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s00034-024-02762-7","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
引用次数: 0

摘要

现有的雨水条纹去除方法能提供较好的去除效果,但由于视觉质量较差,无法在低照度图像上实现。为了解决这个问题,本文提出了一种新颖的雨痕去除方法,该方法采用了振荡 TGV(ICTGV^{osci}\)正则化的 m 折次卷积和 Retinex 理论,适用于低照度图像。该方法在一些具有挑战性的低光照雨天图像上进行了实验,与最先进的方法相比,证明了所提出方法的效率和灵活性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Low-Light Image Deraining Based on Higher Order Variational Model

The existing rain streaks removal methods provide better deraining results, but it cannot be implemented on the low-light images due to the poor visual quality. To solve this problem, this paper presents a novel rain streaks removal approach using m fold infimal convolution of oscillating TGV(\(ICTGV^{osci}\)) regularization and Retinex theory for low-light images. Experiments on a number of challenging low-light rainy images are presented to demonstrate the efficiency and the flexibility of the proposed approaches in comparison with state-of-the-art methods.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Circuits, Systems and Signal Processing
Circuits, Systems and Signal Processing 工程技术-工程:电子与电气
CiteScore
4.80
自引率
13.00%
发文量
321
审稿时长
4.6 months
期刊介绍: Rapid developments in the analog and digital processing of signals for communication, control, and computer systems have made the theory of electrical circuits and signal processing a burgeoning area of research and design. The aim of Circuits, Systems, and Signal Processing (CSSP) is to help meet the needs of outlets for significant research papers and state-of-the-art review articles in the area. The scope of the journal is broad, ranging from mathematical foundations to practical engineering design. It encompasses, but is not limited to, such topics as linear and nonlinear networks, distributed circuits and systems, multi-dimensional signals and systems, analog filters and signal processing, digital filters and signal processing, statistical signal processing, multimedia, computer aided design, graph theory, neural systems, communication circuits and systems, and VLSI signal processing. The Editorial Board is international, and papers are welcome from throughout the world. The journal is devoted primarily to research papers, but survey, expository, and tutorial papers are also published. Circuits, Systems, and Signal Processing (CSSP) is published twelve times annually.
期刊最新文献
Squeeze-and-Excitation Self-Attention Mechanism Enhanced Digital Audio Source Recognition Based on Transfer Learning Recursive Windowed Variational Mode Decomposition Discrete-Time Delta-Sigma Modulator with Successively Approximating Register ADC Assisted Analog Feedback Technique Individually Weighted Modified Logarithmic Hyperbolic Sine Curvelet Based Recursive FLN for Nonlinear System Identification Event-Triggered $$H_{\infty }$$ Filtering for A Class of Nonlinear Systems Under DoS Attacks
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1