{"title":"通过量化和熵编码改进分形图像压缩方案","authors":"M. Ghazel, A. Khandani, E. Vrscay","doi":"10.1109/CCECE.1998.685583","DOIUrl":null,"url":null,"abstract":"We explore the transform coefficients of various fractal-based schemes for statistical dependence and exploit correlations to improve the compression capabilities of these schemes. In most of the standard fractal-based schemes, the transform coefficients exhibit a degree of linear dependence that can be exploited by using an appropriate vector quantizer such as the LBG algorithm. Additional compression is achieved by lossless Huffman coding of the quantized coefficients.","PeriodicalId":177613,"journal":{"name":"Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341)","volume":"254 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Improving fractal image compression schemes through quantization and entropy coding\",\"authors\":\"M. Ghazel, A. Khandani, E. Vrscay\",\"doi\":\"10.1109/CCECE.1998.685583\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We explore the transform coefficients of various fractal-based schemes for statistical dependence and exploit correlations to improve the compression capabilities of these schemes. In most of the standard fractal-based schemes, the transform coefficients exhibit a degree of linear dependence that can be exploited by using an appropriate vector quantizer such as the LBG algorithm. Additional compression is achieved by lossless Huffman coding of the quantized coefficients.\",\"PeriodicalId\":177613,\"journal\":{\"name\":\"Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341)\",\"volume\":\"254 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1998-05-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CCECE.1998.685583\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Conference Proceedings. IEEE Canadian Conference on Electrical and Computer Engineering (Cat. No.98TH8341)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCECE.1998.685583","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Improving fractal image compression schemes through quantization and entropy coding
We explore the transform coefficients of various fractal-based schemes for statistical dependence and exploit correlations to improve the compression capabilities of these schemes. In most of the standard fractal-based schemes, the transform coefficients exhibit a degree of linear dependence that can be exploited by using an appropriate vector quantizer such as the LBG algorithm. Additional compression is achieved by lossless Huffman coding of the quantized coefficients.