{"title":"基于模糊划分的曲波和小波去噪算法","authors":"Naizhang Feng, Liyong Ma, Yi Shen","doi":"10.1109/CIS.WORKSHOPS.2007.10","DOIUrl":null,"url":null,"abstract":"Curvelets denoise approach has been proposed to obtain high quality result images recently. But artifacts often appear in the result images after applying curvelets denoise approach. A fuzzy partition based denoise algorithm was proposed to suppress the artifacts employing result images of curvelets and hidden Markov tree based wavelets denoise approaches. After fuzzy partition was applied to the image support, the local properties of the fuzzy windows were estimated. Image fusion was applied to the curvelets and wavelets result images where the weights were decided by the local properties. Experimental results demonstrated that the algorithm improved the visual quality of result images efficiently and suppressed the artifacts in result images evidently.","PeriodicalId":409737,"journal":{"name":"2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Fuzzy Partition Based Curvelets and Wavelets Denoise Algorithm\",\"authors\":\"Naizhang Feng, Liyong Ma, Yi Shen\",\"doi\":\"10.1109/CIS.WORKSHOPS.2007.10\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Curvelets denoise approach has been proposed to obtain high quality result images recently. But artifacts often appear in the result images after applying curvelets denoise approach. A fuzzy partition based denoise algorithm was proposed to suppress the artifacts employing result images of curvelets and hidden Markov tree based wavelets denoise approaches. After fuzzy partition was applied to the image support, the local properties of the fuzzy windows were estimated. Image fusion was applied to the curvelets and wavelets result images where the weights were decided by the local properties. Experimental results demonstrated that the algorithm improved the visual quality of result images efficiently and suppressed the artifacts in result images evidently.\",\"PeriodicalId\":409737,\"journal\":{\"name\":\"2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)\",\"volume\":\"62 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIS.WORKSHOPS.2007.10\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Computational Intelligence and Security Workshops (CISW 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIS.WORKSHOPS.2007.10","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fuzzy Partition Based Curvelets and Wavelets Denoise Algorithm
Curvelets denoise approach has been proposed to obtain high quality result images recently. But artifacts often appear in the result images after applying curvelets denoise approach. A fuzzy partition based denoise algorithm was proposed to suppress the artifacts employing result images of curvelets and hidden Markov tree based wavelets denoise approaches. After fuzzy partition was applied to the image support, the local properties of the fuzzy windows were estimated. Image fusion was applied to the curvelets and wavelets result images where the weights were decided by the local properties. Experimental results demonstrated that the algorithm improved the visual quality of result images efficiently and suppressed the artifacts in result images evidently.