{"title":"Low-Light Image Enhancement Algorithm Based on Improved MSRCP With Chromaticity Preservation","authors":"Wenjian Feng, Zhiwen Wang, Chunmiao Wei, Xinhui Jiang, Yuhang Wang, Jiexia Huang","doi":"10.1002/cpe.8396","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>In response to the issues of poor sharpness and low information entropy in traditional MSRCP (Multi-Scale Retinex with Color Restoration) algorithms for image enhancement, we propose an improved MSRCP algorithm for low-light image enhancement with chromaticity preservation. First, we replaced the extrema calculation method in the color restoration function with a calculation method based on clipped pixel ratios. Then, we combined guided filtering and Gaussian filtering to calculate the incident component. Finally, we conducted experiments using six different low-light images and compared the results with the traditional MSRCP algorithm, such as SSR, MSR, MSRCR, and MSRCP. The experimental results show that our method improved the sharpness and information entropy values in the five comparison images by 5.6%–35.6% and 0.18%–15.3%, respectively.</p>\n </div>","PeriodicalId":55214,"journal":{"name":"Concurrency and Computation-Practice & Experience","volume":"37 4-5","pages":""},"PeriodicalIF":1.5000,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Concurrency and Computation-Practice & Experience","FirstCategoryId":"94","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/cpe.8396","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
In response to the issues of poor sharpness and low information entropy in traditional MSRCP (Multi-Scale Retinex with Color Restoration) algorithms for image enhancement, we propose an improved MSRCP algorithm for low-light image enhancement with chromaticity preservation. First, we replaced the extrema calculation method in the color restoration function with a calculation method based on clipped pixel ratios. Then, we combined guided filtering and Gaussian filtering to calculate the incident component. Finally, we conducted experiments using six different low-light images and compared the results with the traditional MSRCP algorithm, such as SSR, MSR, MSRCR, and MSRCP. The experimental results show that our method improved the sharpness and information entropy values in the five comparison images by 5.6%–35.6% and 0.18%–15.3%, respectively.
针对传统MSRCP （Multi-Scale Retinex with Color Restoration）图像增强算法清晰度差、信息熵低的问题，提出了一种基于色度保持的弱光图像增强改进MSRCP算法。首先，我们将颜色恢复函数中的极值计算方法替换为基于裁剪像素比的计算方法。然后，我们结合制导滤波和高斯滤波来计算入射分量。最后，利用6幅不同的低光图像进行实验，并与传统的MSRCP算法（SSR、MSR、MSRCR和MSRCP）进行比较。实验结果表明，该方法将5幅对比图像的清晰度和信息熵值分别提高了5.6% ~ 35.6%和0.18% ~ 15.3%。
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