Wavelet Coefficient Computation with Optimal Prefiltering

Xiang Gen Xia; C. C. Jay Kuo; Zhen Zhang

doi:10.1109/78.301858

Wavelet Coefficient Computation with Optimal Prefiltering

Xiang Gen Xia, C. C. Jay Kuo, Zhen Zhang

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22 引用（Scopus）

摘要

Discrete wavelet transform (DWT) is often used to approximate wavelet series transform (WST) and continuous wavelet transform (CWT), since it can be computed numerically. In this research, we first study the accuracy of the computed DWT coefficients obtained from the Shensa algorithm as an approximate of the WST coefficients. Based on the accuracy analysis, we then propose a procedure to design optimal FIR prefilters used in the Shensa algorithm to reduce the approximation error. Finally, numerical examples are presented to demonstrate the performance of the optimal FIR prefilters.

源语言	英语
页（从-至）	2191-2197
页数	7
期刊	IEEE Transactions on Signal Processing
卷	42
期	8
DOI	https://doi.org/10.1109/78.301858
出版状态	已出版 - 8月 1994
已对外发布	是

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Xia, X. G., Jay Kuo, C. C., & Zhang, Z. (1994). Wavelet Coefficient Computation with Optimal Prefiltering. IEEE Transactions on Signal Processing, 42(8), 2191-2197. https://doi.org/10.1109/78.301858

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AB - Discrete wavelet transform (DWT) is often used to approximate wavelet series transform (WST) and continuous wavelet transform (CWT), since it can be computed numerically. In this research, we first study the accuracy of the computed DWT coefficients obtained from the Shensa algorithm as an approximate of the WST coefficients. Based on the accuracy analysis, we then propose a procedure to design optimal FIR prefilters used in the Shensa algorithm to reduce the approximation error. Finally, numerical examples are presented to demonstrate the performance of the optimal FIR prefilters.

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Wavelet Coefficient Computation with Optimal Prefiltering

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