Performance analysis of integer wavelet transform for image compression

Chesta Jain, Vijay K. Chaudhary, Kapil Jain, S. Karsoliya
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引用次数: 26

Abstract

For image compression, it is very necessary that the selection of transform should reduce the size of the resultant data as compared to the original data set. In this paper, a new lossless image compression method is proposed. For continuous and discrete time cases, wavelet transform and wavelet packet transform has emerged as popular techniques. While integer wavelet using the lifting scheme significantly reduces the computation time, we propose a completely new approach for further speeding up the computation. First, wavelet packet transform (WPT) and lifting scheme (LS) are described. Then an application of the LS to WPT is presented which leads to the generation of integer wavelet packet transform (IWPT). The proposed method, Integer Wavelet Packet Transform (IWPT) yields a representation which can be lossless, as it maps an integer valued sequence onto the integer valued coefficients. The idea of Wavelet Packet Tree is used to transform the still and color images. IWPT tree can be built by iterating the single wavelet decomposition step on both the low-pass and high-pass branches, with rounding off in order to achieve the integer transforms. Thus, the proposed method provides good compression ratio.
整数小波变换在图像压缩中的性能分析
对于图像压缩,变换的选择应该使结果数据相对于原始数据集的大小减小,这是非常必要的。本文提出了一种新的无损图像压缩方法。对于连续时间和离散时间的情况,小波变换和小波包变换已经成为流行的技术。整数小波的提升方案大大减少了计算时间,我们提出了一种全新的方法来进一步加快计算速度。首先,介绍了小波包变换(WPT)和提升方案(LS)。在此基础上,提出了一种将小波包变换应用于小波包变换的方法,从而产生整数小波包变换。所提出的方法,整数小波包变换(IWPT)产生一种可以无损的表示,因为它将整数值序列映射到整数值系数上。利用小波包树的思想对静止图像和彩色图像进行变换。IWPT树可以通过在低通和高通分支上迭代单个小波分解步骤来构建,并舍入以实现整数变换。因此,该方法具有良好的压缩比。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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