{"title":"图像压缩的最小二乘网格模型","authors":"Iciar Alvarez-Cascos, Yongyi Yang","doi":"10.1109/ICIP.2004.1419488","DOIUrl":null,"url":null,"abstract":"In this work we explore the use of a content-adaptive mesh model for image compression. We first model the image to be compressed by a quadtree mesh representation, in which the nodal values are determined using a least squares fit. The resulting mesh structure is coded using a 4-ary tree and the mesh nodal values are coded using a hierarchical predictive coding scheme. Our experimental results demonstrate that the proposed approach can achieve good compression performance and can significantly outperform JPEG both subjectively and objectively in low bit-rate applications.","PeriodicalId":184798,"journal":{"name":"2004 International Conference on Image Processing, 2004. ICIP '04.","volume":"168 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Least-squares mesh model for image compression\",\"authors\":\"Iciar Alvarez-Cascos, Yongyi Yang\",\"doi\":\"10.1109/ICIP.2004.1419488\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work we explore the use of a content-adaptive mesh model for image compression. We first model the image to be compressed by a quadtree mesh representation, in which the nodal values are determined using a least squares fit. The resulting mesh structure is coded using a 4-ary tree and the mesh nodal values are coded using a hierarchical predictive coding scheme. Our experimental results demonstrate that the proposed approach can achieve good compression performance and can significantly outperform JPEG both subjectively and objectively in low bit-rate applications.\",\"PeriodicalId\":184798,\"journal\":{\"name\":\"2004 International Conference on Image Processing, 2004. ICIP '04.\",\"volume\":\"168 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-10-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2004 International Conference on Image Processing, 2004. ICIP '04.\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICIP.2004.1419488\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2004 International Conference on Image Processing, 2004. ICIP '04.","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2004.1419488","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this work we explore the use of a content-adaptive mesh model for image compression. We first model the image to be compressed by a quadtree mesh representation, in which the nodal values are determined using a least squares fit. The resulting mesh structure is coded using a 4-ary tree and the mesh nodal values are coded using a hierarchical predictive coding scheme. Our experimental results demonstrate that the proposed approach can achieve good compression performance and can significantly outperform JPEG both subjectively and objectively in low bit-rate applications.