{"title":"小波系数在自动建模和图像编码中的聚类上下文特性","authors":"J. Lehtinen, J. Kivijärvi","doi":"10.1109/ICIAP.2001.957000","DOIUrl":null,"url":null,"abstract":"An algorithm for automatic modelling of wavelet coefficients from context properties is presented. The algorithm is used to implement an image coder, in order to demonstrate its image coding efficiency. The modelling of wavelet co-efficients is performed by partitioning the weighted context property space to regions. Each of the regions has a dynamic probability distribution stating the predictions of the modeled co-efficients. The coding performance of the algorithm is compared to other efficient wavelet-based image compression methods.","PeriodicalId":365627,"journal":{"name":"Proceedings 11th International Conference on Image Analysis and Processing","volume":"129 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2001-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Clustering context properties of wavelet coefficients in automatic modelling and image coding\",\"authors\":\"J. Lehtinen, J. Kivijärvi\",\"doi\":\"10.1109/ICIAP.2001.957000\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An algorithm for automatic modelling of wavelet coefficients from context properties is presented. The algorithm is used to implement an image coder, in order to demonstrate its image coding efficiency. The modelling of wavelet co-efficients is performed by partitioning the weighted context property space to regions. Each of the regions has a dynamic probability distribution stating the predictions of the modeled co-efficients. The coding performance of the algorithm is compared to other efficient wavelet-based image compression methods.\",\"PeriodicalId\":365627,\"journal\":{\"name\":\"Proceedings 11th International Conference on Image Analysis and Processing\",\"volume\":\"129 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2001-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings 11th International Conference on Image Analysis and Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIAP.2001.957000\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings 11th International Conference on Image Analysis and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIAP.2001.957000","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Clustering context properties of wavelet coefficients in automatic modelling and image coding
An algorithm for automatic modelling of wavelet coefficients from context properties is presented. The algorithm is used to implement an image coder, in order to demonstrate its image coding efficiency. The modelling of wavelet co-efficients is performed by partitioning the weighted context property space to regions. Each of the regions has a dynamic probability distribution stating the predictions of the modeled co-efficients. The coding performance of the algorithm is compared to other efficient wavelet-based image compression methods.
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