{"title":"脱轨算法的比较分析","authors":"Radu Grigoraş, I. Ciocoiu","doi":"10.1109/ISSCS.2017.8034929","DOIUrl":null,"url":null,"abstract":"The paper reports comparative performances of five distinct algorithms used for rain removal from single images. Both synthetic and real images are considered, while taking into account standard figures of merit such as PSNR, VIF and SSIM. The experiments revealed that the Gaussian Mixture Model based approach yields best performances in terms of visual quality.","PeriodicalId":338255,"journal":{"name":"2017 International Symposium on Signals, Circuits and Systems (ISSCS)","volume":"241 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Comparative analysis of deraining algorithms\",\"authors\":\"Radu Grigoraş, I. Ciocoiu\",\"doi\":\"10.1109/ISSCS.2017.8034929\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper reports comparative performances of five distinct algorithms used for rain removal from single images. Both synthetic and real images are considered, while taking into account standard figures of merit such as PSNR, VIF and SSIM. The experiments revealed that the Gaussian Mixture Model based approach yields best performances in terms of visual quality.\",\"PeriodicalId\":338255,\"journal\":{\"name\":\"2017 International Symposium on Signals, Circuits and Systems (ISSCS)\",\"volume\":\"241 4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 International Symposium on Signals, Circuits and Systems (ISSCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISSCS.2017.8034929\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 International Symposium on Signals, Circuits and Systems (ISSCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISSCS.2017.8034929","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper reports comparative performances of five distinct algorithms used for rain removal from single images. Both synthetic and real images are considered, while taking into account standard figures of merit such as PSNR, VIF and SSIM. The experiments revealed that the Gaussian Mixture Model based approach yields best performances in terms of visual quality.