'Analytic' wavelet thresholding
成果类型：
Article
署名作者：
Olhede, SC; Walden, AT
署名单位：
Imperial College London
刊物名称：
BIOMETRIKA
ISSN/ISSBN：
0006-3444
DOI：
10.1093/biomet/91.4.955
发表日期：
2004
页码：
955973
关键词：
摘要：
We introduce so-called analytic stationary wavelet transform thresholding where, using the discrete Hilbert transform, we create a complex-valued 'analytic' vector from which an amplitude vector is defined. Thresholding of a real-valued wavelet coefficient at some transform level is carried out according to the corresponding value in this amplitude vector; relevant statistical results follow from properties of the discrete Hilbert transform. Analytic stationary wavelet transform thresholding is found to produce consistently a reduced mean squared error compared to using standard stationary wavelet transform, or 'cycle spinning', thresholding. For signals with extensive oscillations at some transform levels, this improvement is very marked. Furthermore we show that our thresholding test is invariant to phase shifts in the data, whereas, if complex wavelet filters are being used, the filters must be analytic or anti-analytic at each level of the wavelet transform.