scispace - formally typeset
Search or ask a question
Topic

Harmonic wavelet transform

About: Harmonic wavelet transform is a research topic. Over the lifetime, 9602 publications have been published within this topic receiving 247336 citations.


Papers
More filters
Journal ArticleDOI
TL;DR: It was found that DWT outperformed fast Fourier transform (FFT) in the extraction of important features from the sensor response and, allowed for straightforward gas recognition in feature space.
Abstract: We demonstrate that a single, thermally modulated tungsten oxide-based resistive sensor can discriminate between different vapours. The method uses a novel feature extraction and pattern classification method, which is based on the discrete wavelet transform (DWT). It was found that DWT outperformed fast Fourier transform (FFT) in the extraction of important features from the sensor response and, allowed for straightforward gas recognition in feature space.

71 citations

Journal ArticleDOI
TL;DR: The Stockwell transform (ST), recently developed for geophysics, combines features of the Fourier, Gabor and wavelet transforms; it reveals frequency variation over time or space and is a potentially effective tool to visualize, analyze, and process medical imaging data.
Abstract: The Stockwell transform (ST), recently developed for geophysics, combines features of the Fourier, Gabor and wavelet transforms; it reveals frequency variation over time or space. This valuable information is obtained by Fourier analysis of a small segment of a signal at a time. Localization of the Fourier spectrum is achieved by filtering the signal with frequency-dependent Gaussian scaling windows. This multi-scale time–frequency analysis provides information about which frequencies occur and more importantly when they occur. Furthermore, the Stockwell domain can be directly inferred from the Fourier domain and vice versa. These features make the ST a potentially effective tool to visualize,analyze, and process medical imaging data. The ST has proven useful in noise reduction and tissue texture analysis. Herein, we focus on the theory and effectiveness of the ST for medical imaging. Its effectiveness and comparison with other linear time–frequency transforms, such as the Gabor and wavelet transforms, are discussed and demonstrated using functional magnetic resonance imaging data.

71 citations

Journal ArticleDOI
TL;DR: In this article, an inversion-based algorithm for computing the time-frequency analysis of reflection seismograms using constrained least-squares spectral analysis is formulated and applied to modeled seismic waveforms and real seismic data.
Abstract: An inversion-based algorithm for computing the time-frequency analysis of reflection seismograms using constrained least-squares spectral analysis is formulated and applied to modeled seismic waveforms and real seismic data. The Fourier series coefficients are computed as a function of time directly by inverting a basis of truncated sinusoidal kernels for a moving time window. The method resulted in spectra that have reduced window smearing for a given window length relative to the discrete Fourier transform irrespective of window shape, and a time-frequency analysis with a combination of time and frequency resolution that is superior to the short time Fourier transform and the continuous wavelet transform. The reduction in spectral smoothing enables better determination of the spectral characteristics of interfering reflections within a short window. The degree of resolution improvement relative to the short time Fourier transform increases as window length decreases. As compared with the continu...

71 citations

Journal Article
TL;DR: The wavelet transform appears to be a natural alternative to the decompositions commonly used in fluid dynamics and turbulence (mainly the Fourier decomposition) as mentioned in this paper, and the most attractive properties of wavelets are reviewed and explained using the classical language of turbulence.
Abstract: The basic definitions and the most attractive properties of the wavelet transform are reviewed and explained using the classical language of turbulence The wavelet transform appears to be a natural alternative to the decompositions commonly used in fluid dynamics and turbulence (mainly the Fourier decomposition)

71 citations

Proceedings ArticleDOI
24 Jun 2002
TL;DR: A new and unique system for achieving transform coding aims of coefficient elimination and compensation is developed and demonstrated, based on iterative projection of signals between the image domain and transform domain.
Abstract: Overcomplete transforms, like the dual-tree complex wavelet transform, offer more flexible signal representations than critically-sampled transforms. Large numbers of transform coefficients can be discarded without much reconstruction quality loss by forcing compensatory changes in the remaining coefficients. We develop and demonstrate a new and unique system for achieving these transform coding aims of coefficient elimination and compensation. The system is based on iterative projection of signals between the image domain and transform domain.

71 citations


Network Information
Related Topics (5)
Image processing
229.9K papers, 3.5M citations
82% related
Feature extraction
111.8K papers, 2.1M citations
82% related
Image segmentation
79.6K papers, 1.8M citations
81% related
Support vector machine
73.6K papers, 1.7M citations
80% related
Feature (computer vision)
128.2K papers, 1.7M citations
78% related
Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202323
202274
20213
20207
20196
201831