基于样条小波的提升实现

Gamal Fahmy
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引用次数: 1

摘要

b样条数学函数长期以来一直被用于信号表示。然而,它们最近才被用于信号插值和缩放。b样条可以代表用于信号/图像压缩和多分辨率分析的下一代小波。这是因为它们是灵活的,并且提供了最佳的成本/质量平衡关系。通过改变b样条函数的阶数,我们从线性表示移动到高阶带限表示。b样条也与微分有关,因为它们是系数的离散和连续版本之间的精确数学转换。本文提出了一种基于b样条数学函数的信号/图像分解、分析、合成和重建新技术。对所提出的样条预测的数学解释和推导进行了分析。我们还提出了一种基于提升的b样条图像编码器的实现,并测量了它对压缩质量的影响。本文给出了用该方法对不同b样条阶数的图像进行的大量仿真结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bspline based Wavelets with Lifting Implementation
The Bspline mathematical functions have long been utilized for signal representation. However they have been just recently been used for signal interpolation and zooming. Bsplines can represent the next generation of wavelets for signal/image compression and multi-resolution analysis. This is due to the fact that they are flexible and provide the best cost/quality trade off relationship. By changing the Bspline function order we move from a linear representation to a high order band limited representation. Bsplines are also linked to differentials, as they are the exact mathematical translators between the discrete and continuous versions of the coefficients. In this paper we propose a novel technique for signal/image decomposition, analysis, synthesis and reconstruction based on the Bspline mathematical functions. Mathematical explanation and derivation for the proposed Bspline prediction is analyzed. We also present a lifting based implementation for the proposed Bspline image coder and measure its effect on the compression quality. Extensive simulation results, which have been carried out with the proposed approach on different classes of images with different B-spline orders, are illustrated.
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