{"title":"分形图像编码中的特征差分分类方法","authors":"C. Yisong, Wang Guoping, D. Shihai","doi":"10.1109/ICOSP.2002.1181139","DOIUrl":null,"url":null,"abstract":"In this paper, we present a classification algorithm in fractal image coding. Based on the contraction characteristics of transformations in fractal image coding, the algorithm uses the notion of feature difference to speed up the domain-range matching routine of the coding. The algorithm can effectively exclude pseudo matches during the process of domain-range matching and result in significant improvement of the rate-distortion performance. It can also be easily realized in cooperation with many other speedup schemes.","PeriodicalId":159807,"journal":{"name":"6th International Conference on Signal Processing, 2002.","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Feature difference classification method in fractal image coding\",\"authors\":\"C. Yisong, Wang Guoping, D. Shihai\",\"doi\":\"10.1109/ICOSP.2002.1181139\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we present a classification algorithm in fractal image coding. Based on the contraction characteristics of transformations in fractal image coding, the algorithm uses the notion of feature difference to speed up the domain-range matching routine of the coding. The algorithm can effectively exclude pseudo matches during the process of domain-range matching and result in significant improvement of the rate-distortion performance. It can also be easily realized in cooperation with many other speedup schemes.\",\"PeriodicalId\":159807,\"journal\":{\"name\":\"6th International Conference on Signal Processing, 2002.\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-08-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"6th International Conference on Signal Processing, 2002.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICOSP.2002.1181139\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"6th International Conference on Signal Processing, 2002.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOSP.2002.1181139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Feature difference classification method in fractal image coding
In this paper, we present a classification algorithm in fractal image coding. Based on the contraction characteristics of transformations in fractal image coding, the algorithm uses the notion of feature difference to speed up the domain-range matching routine of the coding. The algorithm can effectively exclude pseudo matches during the process of domain-range matching and result in significant improvement of the rate-distortion performance. It can also be easily realized in cooperation with many other speedup schemes.
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