N. Ponomarenko, K. Egiazarian, V. Lukin, J. Astola
{"title":"压缩图像块意味着使用Delaunay三角剖分和预测的非等块大小分区方案","authors":"N. Ponomarenko, K. Egiazarian, V. Lukin, J. Astola","doi":"10.1109/DCC.2002.1000011","DOIUrl":null,"url":null,"abstract":"Summary form only given. An approach based on applying Delaunay triangulation to compression of mean values of image blocks that have non-identical shape and size is proposed. It can be useful for image compression methods that require the use of image partition schemes with non-equal block size like fractal and DCT-based image coding. Several methods of block mean value coding are considered. In particular, the drawbacks of using quantization with further redundancy elimination by entropy coders are discussed. Another considered method is the forming of the block mean value image and its further compression by lossy coders. Finally, the motivations in favor of Delaunay triangulation application to block mean value image coding are presented.","PeriodicalId":420897,"journal":{"name":"Proceedings DCC 2002. Data Compression Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2002-04-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Compression of image block means for non-equal block size partition schemes using Delaunay triangulation and prediction\",\"authors\":\"N. Ponomarenko, K. Egiazarian, V. Lukin, J. Astola\",\"doi\":\"10.1109/DCC.2002.1000011\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary form only given. An approach based on applying Delaunay triangulation to compression of mean values of image blocks that have non-identical shape and size is proposed. It can be useful for image compression methods that require the use of image partition schemes with non-equal block size like fractal and DCT-based image coding. Several methods of block mean value coding are considered. In particular, the drawbacks of using quantization with further redundancy elimination by entropy coders are discussed. Another considered method is the forming of the block mean value image and its further compression by lossy coders. Finally, the motivations in favor of Delaunay triangulation application to block mean value image coding are presented.\",\"PeriodicalId\":420897,\"journal\":{\"name\":\"Proceedings DCC 2002. Data Compression Conference\",\"volume\":\"41 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2002-04-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings DCC 2002. Data Compression Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.2002.1000011\",\"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 DCC 2002. Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.2002.1000011","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Compression of image block means for non-equal block size partition schemes using Delaunay triangulation and prediction
Summary form only given. An approach based on applying Delaunay triangulation to compression of mean values of image blocks that have non-identical shape and size is proposed. It can be useful for image compression methods that require the use of image partition schemes with non-equal block size like fractal and DCT-based image coding. Several methods of block mean value coding are considered. In particular, the drawbacks of using quantization with further redundancy elimination by entropy coders are discussed. Another considered method is the forming of the block mean value image and its further compression by lossy coders. Finally, the motivations in favor of Delaunay triangulation application to block mean value image coding are presented.