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

机译:用于二维多级分解的局部小波变换实现与最佳行列算法

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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. 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新的用于实现基于卷积的小波变换的二叉树分解的方法,称为局部小波变换(LWT)。尽管它产生与转换的经典行-列实现完全相同的结果,但它具有许多实现上的好处。通过将我们的LWT的C实现与提升方案行列算法的最佳C实现进行比较,首次针对基于通用处理器的体系结构通过实验展示了这一事实。在典型的Intel Pentium处理器家族中,使用9/7滤波器对对正向多级二叉树分解进行了比较。

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