Applications of sampling theorems in wavelet spaces to multiresolution visualization and data segmentation

Dzu K. Le

doi:10.1117/12.217577

1 September 1995 Applications of sampling theorems in wavelet spaces to multiresolution visualization and data segmentation

Dzu K. Le

Author Affiliations +

Proceedings Volume 2569, Wavelet Applications in Signal and Image Processing III; (1995) https://doi.org/10.1117/12.217577
Event: SPIE's 1995 International Symposium on Optical Science, Engineering, and Instrumentation, 1995, San Diego, CA, United States

Abstract

Sampling `theorems' in `wavelet spaces' are very useful for the integration of `wavelet multiresolution' techniques with various time-domain methods for data processing. In this paper, the application potential of `wavelet sampling theorem' will be illustrated through a few examples of dynamical data analysis and filtering. The main results among our recent applications of the wavelet sampling principles for data processing include the `compact- harmonic wavelets' and a new technique for time-frequency analysis. This new analysis technique provides localized wavelet filters with arbitrarily adjustable frequency-resolution, and the exact reconstruction capability. These filter qualities are both useful and essential for the accurate representation of local power-spectra, and segmentation of signals. These results and underlying ideas are also applicable to the fields of imaging and data compression.

Citation Download Citation

Dzu K. Le "Applications of sampling theorems in wavelet spaces to multiresolution visualization and data segmentation", Proc. SPIE 2569, Wavelet Applications in Signal and Image Processing III, (1 September 1995); https://doi.org/10.1117/12.217577

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