{"title":"基于SPHIT的图像压缩算法研究","authors":"Wei Liu","doi":"10.1109/ICINIS.2010.50","DOIUrl":null,"url":null,"abstract":"An image compression algorithm of higher compression ratio based on SPHIT is proposed and simulated, with studying on the SPHIT algorithm and image compression algorithm. Firstly, the image data is divided into high frequency wavelet coefficients and low frequency wavelet coefficients, through the discrete wavelet transform. Secondly, the wavelet coefficients, which are processed and decomposed to several blocks, pass SPHIT coding, according to the compression ratio of image to adjust the SPHIT output coding stream. Finally, the original image is reconstructed by the SPHIT decoding algorithm and inverse wavelet transform. Simulating results show that a higher Peak Signal to Noise Ratio (PSNR) in proposed algorithm than traditional SPHIT algorithm is obtained in the same compression ratio of the image.","PeriodicalId":319379,"journal":{"name":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","volume":"51 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"Research on Image Compression Algorithm Based on SPHIT\",\"authors\":\"Wei Liu\",\"doi\":\"10.1109/ICINIS.2010.50\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"An image compression algorithm of higher compression ratio based on SPHIT is proposed and simulated, with studying on the SPHIT algorithm and image compression algorithm. Firstly, the image data is divided into high frequency wavelet coefficients and low frequency wavelet coefficients, through the discrete wavelet transform. Secondly, the wavelet coefficients, which are processed and decomposed to several blocks, pass SPHIT coding, according to the compression ratio of image to adjust the SPHIT output coding stream. Finally, the original image is reconstructed by the SPHIT decoding algorithm and inverse wavelet transform. Simulating results show that a higher Peak Signal to Noise Ratio (PSNR) in proposed algorithm than traditional SPHIT algorithm is obtained in the same compression ratio of the image.\",\"PeriodicalId\":319379,\"journal\":{\"name\":\"2010 Third International Conference on Intelligent Networks and Intelligent Systems\",\"volume\":\"51 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 Third International Conference on Intelligent Networks and Intelligent Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICINIS.2010.50\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 Third International Conference on Intelligent Networks and Intelligent Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICINIS.2010.50","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Research on Image Compression Algorithm Based on SPHIT
An image compression algorithm of higher compression ratio based on SPHIT is proposed and simulated, with studying on the SPHIT algorithm and image compression algorithm. Firstly, the image data is divided into high frequency wavelet coefficients and low frequency wavelet coefficients, through the discrete wavelet transform. Secondly, the wavelet coefficients, which are processed and decomposed to several blocks, pass SPHIT coding, according to the compression ratio of image to adjust the SPHIT output coding stream. Finally, the original image is reconstructed by the SPHIT decoding algorithm and inverse wavelet transform. Simulating results show that a higher Peak Signal to Noise Ratio (PSNR) in proposed algorithm than traditional SPHIT algorithm is obtained in the same compression ratio of the image.