{"title":"一种基于dct的分形图像压缩方法","authors":"Chong Fu, Zhi-liang Zhu","doi":"10.1109/IWCFTA.2009.99","DOIUrl":null,"url":null,"abstract":"Fractal coding is a potential image compression scheme, which has the advantages of relatively high compression ratios and good reconstruction fidelity. However, the high computational complexity of fractal image encoding greatly restricts its application. This paper proposes a DCT-based fractal image coding method, which improves the self-similarities exploiting scheme. The range and domain blocks are divided into three classes based on their DCT lower frequency coefficients, and only the domain blocks with the same class to the range block are calculated during best match exploiting process. Experimental results show that compared with standard fractal coding scheme, the encoding time is significantly reduced and the PSNR of the reconstructed image is also improved.","PeriodicalId":279256,"journal":{"name":"2009 International Workshop on Chaos-Fractals Theories and Applications","volume":"39 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-11-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"28","resultStr":"{\"title\":\"A DCT-Based Fractal Image Compression Method\",\"authors\":\"Chong Fu, Zhi-liang Zhu\",\"doi\":\"10.1109/IWCFTA.2009.99\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Fractal coding is a potential image compression scheme, which has the advantages of relatively high compression ratios and good reconstruction fidelity. However, the high computational complexity of fractal image encoding greatly restricts its application. This paper proposes a DCT-based fractal image coding method, which improves the self-similarities exploiting scheme. The range and domain blocks are divided into three classes based on their DCT lower frequency coefficients, and only the domain blocks with the same class to the range block are calculated during best match exploiting process. Experimental results show that compared with standard fractal coding scheme, the encoding time is significantly reduced and the PSNR of the reconstructed image is also improved.\",\"PeriodicalId\":279256,\"journal\":{\"name\":\"2009 International Workshop on Chaos-Fractals Theories and Applications\",\"volume\":\"39 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-11-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"28\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 International Workshop on Chaos-Fractals Theories and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IWCFTA.2009.99\",\"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 Workshop on Chaos-Fractals Theories and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWCFTA.2009.99","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fractal coding is a potential image compression scheme, which has the advantages of relatively high compression ratios and good reconstruction fidelity. However, the high computational complexity of fractal image encoding greatly restricts its application. This paper proposes a DCT-based fractal image coding method, which improves the self-similarities exploiting scheme. The range and domain blocks are divided into three classes based on their DCT lower frequency coefficients, and only the domain blocks with the same class to the range block are calculated during best match exploiting process. Experimental results show that compared with standard fractal coding scheme, the encoding time is significantly reduced and the PSNR of the reconstructed image is also improved.