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A local wavelet transform implementation versus an optimal row-column algorithm for the 2D multilevel decomposition

机译:局部小波变换实现与2D多级分解的最佳行列算法

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A new method for the implementation of the binary-tree decomposition of the convolution-based wavelet transform, called the Local Wavelet Transform (LWT) has been recently proposed in the literature. While it produces exactly the same results as the classical row-column implementation of the transform, it has many implementation benefits. In this paper, this fact is shown experimentally for the first time for a general-purpose processor-based architecture, by comparing our C implementation of the LWT with an optimal C implementation of the lifting-scheme row-column algorithm. The comparisons are made for the forward multilevel binary-tree decomposition using the 9/7 filter pair, in the typical Intel Pentium processor family.
机译:最近在文献中提出了一种用于实现基于卷积的小波变换的二进制树分解的新方法,称为局部小波变换(LWT)。虽然它与变换的古典行列实现完全相同的结果,但它具有许多实现优势。在本文中,通过将LWT的C实现与提升方案行列算法的最佳C实现进行比较,通过比较我们的LWT的C实现,在实验上示出了这一事实的基于通用处理器的架构。在典型的Intel Pentium处理器系列中,使用9/7滤网对的前向多级二进制树分解进行比较。

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