{"title":"基于纹理保存的图像压缩算法","authors":"Wenbo Wang, Lin Lei","doi":"10.1109/ASEMD.2009.5306652","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a modified SPIHT algorithm based on the Texture Preservation. First, make a pretreatment of piecewise linear transformation to the coefficients of designated high-frequency subbands. By the addition of this step, the small coefficients in texture subband to some extent can be retained. Then improved SPIHT algorithm's ability of label important coefficients. Experiments show that even at low bit-rate modified SPIHT algorithm has good performance on the Texture Preservation.","PeriodicalId":354649,"journal":{"name":"2009 International Conference on Applied Superconductivity and Electromagnetic Devices","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Image compression algorithm based on the texture preservation\",\"authors\":\"Wenbo Wang, Lin Lei\",\"doi\":\"10.1109/ASEMD.2009.5306652\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a modified SPIHT algorithm based on the Texture Preservation. First, make a pretreatment of piecewise linear transformation to the coefficients of designated high-frequency subbands. By the addition of this step, the small coefficients in texture subband to some extent can be retained. Then improved SPIHT algorithm's ability of label important coefficients. Experiments show that even at low bit-rate modified SPIHT algorithm has good performance on the Texture Preservation.\",\"PeriodicalId\":354649,\"journal\":{\"name\":\"2009 International Conference on Applied Superconductivity and Electromagnetic Devices\",\"volume\":\"72 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-10-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Conference on Applied Superconductivity and Electromagnetic Devices\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASEMD.2009.5306652\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 International Conference on Applied Superconductivity and Electromagnetic Devices","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASEMD.2009.5306652","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Image compression algorithm based on the texture preservation
In this paper, we propose a modified SPIHT algorithm based on the Texture Preservation. First, make a pretreatment of piecewise linear transformation to the coefficients of designated high-frequency subbands. By the addition of this step, the small coefficients in texture subband to some extent can be retained. Then improved SPIHT algorithm's ability of label important coefficients. Experiments show that even at low bit-rate modified SPIHT algorithm has good performance on the Texture Preservation.