Yang Yu, Heng Qiao, Zhi Fan, Fei Li, Ningyi Geng, Long Wang, J. Sun, Xuke Zhong
{"title":"Weakly Illumination Image Enhancement Algorithm in GIS Cavity","authors":"Yang Yu, Heng Qiao, Zhi Fan, Fei Li, Ningyi Geng, Long Wang, J. Sun, Xuke Zhong","doi":"10.1109/CACRE58689.2023.10208889","DOIUrl":null,"url":null,"abstract":"This paper proposes a dual-frequency image fusion algorithm to address the problem of poor preservation of image naturalness in GIS cavities. Firstly, the low-frequency image is obtained by low-pass filtering, and using an improved illumination estimating algorithm to improve low-frequency image brightness; At the same time, using homomorphic high-pass filtering suppresses the low-frequency components and enhances the high-frequency components of the image, and high-frequency image with increased details and uniform illumination is obtained; Then, linear fusion is used to perform linear fusion on the enhanced high and low-frequency images; Finally, experimental verification was conducted in GIS cavities environment, and the effectiveness of the image enhancement algorithm was verified by comparing multiple image evaluation indicators.","PeriodicalId":447007,"journal":{"name":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 8th International Conference on Automation, Control and Robotics Engineering (CACRE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CACRE58689.2023.10208889","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
This paper proposes a dual-frequency image fusion algorithm to address the problem of poor preservation of image naturalness in GIS cavities. Firstly, the low-frequency image is obtained by low-pass filtering, and using an improved illumination estimating algorithm to improve low-frequency image brightness; At the same time, using homomorphic high-pass filtering suppresses the low-frequency components and enhances the high-frequency components of the image, and high-frequency image with increased details and uniform illumination is obtained; Then, linear fusion is used to perform linear fusion on the enhanced high and low-frequency images; Finally, experimental verification was conducted in GIS cavities environment, and the effectiveness of the image enhancement algorithm was verified by comparing multiple image evaluation indicators.