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Wavelets and Wavelet Transform

2017
Wavelet transforms are the most powerful and the most widely used tool in the field of image processing. Wavelet transform has received considerable attention in the field of image processing due to its flexibility in representing non-stationary image signals and its ability in adapting to human visual characteristics. Wavelet transform is an efficient
Soohwan Yu, Aparna Vyas, Joonki Paik
openaire   +2 more sources

Wavelet and wavelet Stieltjes transforms

Proceedings of 32nd IEEE Conference on Decision and Control, 2002
Some fundamental and useful properties of wavelet transforms are presented. A unified approach for both discrete and continuous time-frequency localization is introduced. >
Jie Chen   +3 more
openaire   +2 more sources

Wavelets, Wavelet Filters, and Wavelet Transforms [PDF]

open access: possible, 2013
Spectral characteristics of speech are known to be particularly useful in describing a speech signal such that it can be efficiently reconstructed after coding or identified for recognition. The wavelets are considered one of such efficient methods for representing the spectrum of speech signals.
openaire   +1 more source

EXTENDED WAVELET TRANSFORMS

International Journal of Geometric Methods in Modern Physics, 2006
We introduce the notion of extended wavelet transform for locally compact topological groups that are semidirect products with abelian normal factor, and we study its main properties. In particular, we show that this notion allows to define a weak wavelet transform — enjoying 'essentially' the same properties as a standard wavelet transform ...
openaire   +3 more sources

The Secure Wavelet Transform

Journal of Real-Time Image Processing, 2010
There has been an increasing concern for the security of multimedia transactions over real-time embedded systems. Partial and selective encryption schemes have been proposed in the research literature, but these schemes significantly increase the computation cost leading to tradeoffs in system latency, throughput, hardware requirements and power usage.
Joseph Zambreno, Amit Pande
openaire   +1 more source

Automatic microseismic denoising and onset detection using the synchrosqueezed continuous wavelet transform

, 2016
Typical microseismic data recorded by surface arrays are characterized by low signal-to-noise ratios (S/Ns) and highly nonstationary noise that make it difficult to detect small events.
S. Mousavi, C. Langston, S. Horton
semanticscholar   +1 more source

Discrete Wavelets and Fast Wavelet Transform

1991
The wavelet analysis, introduced by J. MORLET and Y. MEYER in the middle of the eighties, is a processus of time-frequency (or time-scale) analysis which consists of decomposing a signal into a basis of functions (o jk ) called wavelets. These wavelets are in turn deduced from the analyzing wavelet o by dilatations and translations. More precisely:
Bonnet, Pierre, Rémond, Didier
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Multisensor Image Fusion Using the Wavelet Transform

CVGIP: Graphical Models and Image Processing, 1995
The goal of image fusion is to integrate complementary information from multisensor data such that the new images are more suitable for the purpose of human visual perception and computer-processing tasks such as segmentation, feature extraction, and ...
Hui Li, B. S. Manjunath, S. Mitra
semanticscholar   +1 more source

Fractional wavelet transform

Applied Optics, 1997
The wavelet transform, which has had a growing importance in signal and image processing, has been generalized by association with both the wavelet transform and the fractional Fourier transform. Possible implementations of the new transformation are in image compression, image transmission, transient signal processing, etc.
Javier Garcia   +4 more
openaire   +3 more sources

The Wavelet Transforms

2017
Historically, the concept of wavelets started to appear more frequently only in the early 1980s. This new concept can be viewed as a synthesis of various ideas originating from different disciplines including mathematics, physics, and engineering. One of the main reasons for the discovery of wavelets and wavelet transforms is that the Fourier transform
Lokenath Debnath, Firdous A. Shah
openaire   +2 more sources

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