{"title":"基于平铺运算的SPIHT算法分析","authors":"G. Sadashivappa, M. Jayakar, K. A. Babu","doi":"10.1109/ICSAP.2010.34","DOIUrl":null,"url":null,"abstract":"The aim of this paper is to study the performance of wavelet filters, using SPIHT algorithm with tiling operations for image compression. Tiling operations will be useful when images to be compressed are larger in size. Performance of different wavelets on image compression for different level of wavelet decomposition and for different tiling size is studied. Data redundancy is a fundamental issue in image compression. A lossy image compression (SPIHT with tiling) technique which provides a higher level of data reduction but result in a less than perfect reconstruction of original image is implemented here using MATLAB software. Two different resolution of Lena image are used for analysis. Image Quality is measured objectively using PSNR (peak signal to noise ratio) and execution time is verified with respect to the tiling size and level of wavelet decomposition.","PeriodicalId":303366,"journal":{"name":"2010 International Conference on Signal Acquisition and Processing","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Analysis of SPIHT Algorithm Using Tiling Operations\",\"authors\":\"G. Sadashivappa, M. Jayakar, K. A. Babu\",\"doi\":\"10.1109/ICSAP.2010.34\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The aim of this paper is to study the performance of wavelet filters, using SPIHT algorithm with tiling operations for image compression. Tiling operations will be useful when images to be compressed are larger in size. Performance of different wavelets on image compression for different level of wavelet decomposition and for different tiling size is studied. Data redundancy is a fundamental issue in image compression. A lossy image compression (SPIHT with tiling) technique which provides a higher level of data reduction but result in a less than perfect reconstruction of original image is implemented here using MATLAB software. Two different resolution of Lena image are used for analysis. Image Quality is measured objectively using PSNR (peak signal to noise ratio) and execution time is verified with respect to the tiling size and level of wavelet decomposition.\",\"PeriodicalId\":303366,\"journal\":{\"name\":\"2010 International Conference on Signal Acquisition and Processing\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-02-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Signal Acquisition and Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSAP.2010.34\",\"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 International Conference on Signal Acquisition and Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSAP.2010.34","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
摘要
本文的目的是研究小波滤波器的性能,利用SPIHT算法和平铺运算进行图像压缩。当要压缩的图像尺寸较大时,平铺操作将非常有用。研究了不同小波分解级别和不同铺层尺寸下不同小波对图像压缩的性能。数据冗余是图像压缩中的一个基本问题。使用MATLAB软件实现了一种有损图像压缩(SPIHT with tiling)技术,该技术提供了更高水平的数据缩减,但导致原始图像的重建不完美。采用两种不同分辨率的Lena图像进行分析。利用峰值信噪比客观地衡量图像质量,并根据小波分解的平铺大小和程度来验证执行时间。
Analysis of SPIHT Algorithm Using Tiling Operations
The aim of this paper is to study the performance of wavelet filters, using SPIHT algorithm with tiling operations for image compression. Tiling operations will be useful when images to be compressed are larger in size. Performance of different wavelets on image compression for different level of wavelet decomposition and for different tiling size is studied. Data redundancy is a fundamental issue in image compression. A lossy image compression (SPIHT with tiling) technique which provides a higher level of data reduction but result in a less than perfect reconstruction of original image is implemented here using MATLAB software. Two different resolution of Lena image are used for analysis. Image Quality is measured objectively using PSNR (peak signal to noise ratio) and execution time is verified with respect to the tiling size and level of wavelet decomposition.