The generalized Haar-Walsh transform

The generalized Haar-Walsh transform
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DOI:
10.1109/ssp.2014.6884678
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发表时间:
2014-06
期刊:
2014 IEEE Workshop on Statistical Signal Processing (SSP)
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通讯作者:
Jeff Irion;N. Saito
Jeff Irion;N. Saito
中科院分区:
其他
文献类型:
--
作者:
Jeff Irion;N. Saito

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我们介绍了一种新的多尺度变换的信号图,这是一个推广的经典Haar和Walsh-Hadamard变换。使用递归分区的图形和连续的平均和差分操作,我们的变换生成一个过完备字典的标准正交基。我们描述了如何适应经典的最佳基搜索算法,以这种设置,并显示初步的去噪实验的结果。
We introduce a novel multiscale transform for signals on graphs which is a generalization of the classical Haar and Walsh-Hadamard Transforms. Using a recursive partitioning of the graph and successive averaging and differencing operations, our transform generates an overcomplete dictionary of orthonormal bases. We describe how to adapt the classical best-basis search algorithm to this setting, and show results from preliminary denoising experiments.