Optimal wavelet design via multiresolutional parametric spectral estimation

Min Xie; A. A. (Louis) Beex

doi:10.1117/12.205425

6 April 1995 Optimal wavelet design via multiresolutional parametric spectral estimation

Min Xie, A. A. (Louis) Beex

Proceedings Volume 2491, Wavelet Applications II; (1995) https://doi.org/10.1117/12.205425
Event: SPIE's 1995 Symposium on OE/Aerospace Sensing and Dual Use Photonics, 1995, Orlando, FL, United States

Abstract

Due to the fact that linearly dependent wavelet transforms are inefficient in computation and storage, the most popular discrete wavelet transforms (DWT) use orthonormal basis decompositions (ODWT). However, there are several problems related to ODWT: as a time- frequency analyzer, the time-frequency resolution and localization of ODWT are poor; from a spectral analysis point of view, the ODWT produces a distorted spectrum with energy leaking, aliasing, and magnitude distortion; to produce a reasonable time-varying spectrum, the signal is required to be octave-distributed with a spectral shape matching the spectra of the wavelets. To overcome these problems, a new approach for designing the optimal wavelet is proposed. Using the multiresolution parametric spectral estimator, the new method continuously tracks the time-varying signal to adapt the optimal wavelets, and yields high resolution, localization, and fidelity for the resulting time-frequency decomposition. When the optimal wavelets act as matched filters they can greatly reduce broadband background noise in the decomposition process.

Citation Download Citation

Min Xie and A. A. (Louis) Beex "Optimal wavelet design via multiresolutional parametric spectral estimation", Proc. SPIE 2491, Wavelet Applications II, (6 April 1995); https://doi.org/10.1117/12.205425

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