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Daubechies Wavelets
"... this paper contains a derivation of Coiflets, which are the shortest wavelets with M vanishing moments for both ..."
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this paper contains a derivation of Coiflets, which are the shortest wavelets with M vanishing moments for both
2011 Generalized Daubechies wavelets
 IEEE Trans on Acoustics, Speech, and Signal Processing
"... We present a generalization of the Daubechies wavelet family. The context is that of a nonstationary multiresolution analysis — i.e., a sequence of embedded approximation spaces generated by scaling functions that are not necessarily dilates of one another. The constraints that we impose on th ..."
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Cited by 2 (1 self)
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We present a generalization of the Daubechies wavelet family. The context is that of a nonstationary multiresolution analysis — i.e., a sequence of embedded approximation spaces generated by scaling functions that are not necessarily dilates of one another. The constraints that we im
Generalized Daubechies Wavelet Families
, 2007
"... We present a generalization of the orthonormal Daubechies wavelets and of their related biorthogonal flavors (CohenDaubechiesFeauveau, 9/7). Our fundamental constraint is that the scaling functions should reproduce a predefined set of exponential polynomials. This allows one to tune the correspon ..."
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Cited by 11 (3 self)
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We present a generalization of the orthonormal Daubechies wavelets and of their related biorthogonal flavors (CohenDaubechiesFeauveau, 9/7). Our fundamental constraint is that the scaling functions should reproduce a predefined set of exponential polynomials. This allows one to tune
Image Processing with Complex Daubechies Wavelets
 Journal of Mathematical Imaging and Vision
, 1996
"... Analyses based on Symmetric Daubechies Wavelets (SDW) lead to complexvalued multiresolution representations of real signals. After a recall of the construction of the SDW, we present some specific properties of these new types of Daubechies wavelets. We then discuss two applications in image proces ..."
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Cited by 10 (2 self)
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Analyses based on Symmetric Daubechies Wavelets (SDW) lead to complexvalued multiresolution representations of real signals. After a recall of the construction of the SDW, we present some specific properties of these new types of Daubechies wavelets. We then discuss two applications in image
Generalized biorthogonal Daubechies wavelets
"... We propose a generalization of the CohenDaubechiesFeauveau (CDF) and 9/7 biorthogonal wavelet families. This is done within the framework of nonstationary multiresolution analysis, which involves a sequence of embedded approximation spaces generated by scaling functions that are not necessarily d ..."
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We propose a generalization of the CohenDaubechiesFeauveau (CDF) and 9/7 biorthogonal wavelet families. This is done within the framework of nonstationary multiresolution analysis, which involves a sequence of embedded approximation spaces generated by scaling functions that are not necessarily
Image Processing with Complex Daubechies Wavelets
 Journal of Mathematical Imaging and Vision
, 1996
"... Analyses based on Symmetric Daubechies Wavelets (SDW) lead to complexvalued multiresolution representations of real signals. After a recall of the construction of the SDW, we present some specific properties of these new types of Daubechies wavelets. We then discuss two applications in image proces ..."
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Analyses based on Symmetric Daubechies Wavelets (SDW) lead to complexvalued multiresolution representations of real signals. After a recall of the construction of the SDW, we present some specific properties of these new types of Daubechies wavelets. We then discuss two applications in image
Asymptotics and Numerics of Zeros of Polynomials That Are Related to Daubechies Wavelets
, 1997
"... We give asymptotic approximations of the zeros of certain high degree polynomials. The zeros can be used to compute the filter coefficients in the dilation equations which define the compactly supported orthogonal Daubechies wavelets. Computational schemes are presented to obtain the numerical value ..."
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Cited by 5 (0 self)
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We give asymptotic approximations of the zeros of certain high degree polynomials. The zeros can be used to compute the filter coefficients in the dilation equations which define the compactly supported orthogonal Daubechies wavelets. Computational schemes are presented to obtain the numerical
Asymptotics and Numerics of Zeros of Polynomials That Are Related to Daubechies Wavelets
, 1997
"... We give asymptotic approximations of the zeros of certain high degree polynomials. The zeros can be used to compute the filter coefficients in the dilation equations which define the compactly supported orthogonal Daubechies wavelets. Computational schemes are presented to obtain the numerical value ..."
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We give asymptotic approximations of the zeros of certain high degree polynomials. The zeros can be used to compute the filter coefficients in the dilation equations which define the compactly supported orthogonal Daubechies wavelets. Computational schemes are presented to obtain the numerical
Least And Most Disjoint Root Sets For Daubechies Wavelets
, 1999
"... A new set of wavelet filter families has been added to the systematized collection of Daubechies wavelets. This new set includes complex and real, orthogonal and biorthogonal, least and most disjoint families defined using constraints derived from the principle of separably disjoint root sets in the ..."
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Cited by 1 (1 self)
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A new set of wavelet filter families has been added to the systematized collection of Daubechies wavelets. This new set includes complex and real, orthogonal and biorthogonal, least and most disjoint families defined using constraints derived from the principle of separably disjoint root sets
NonLinear Shrinkage Estimation with Complex Daubechies Wavelets
 PROCEEDINGS OF SPIE, WAVELET APPLICATIONS IN SIGNAL AND IMAGE PROCESSING V
, 1997
"... One of the main advantages of the discrete wavelet representation is the nearoptimal estimation of signals corrupted with noise. After the seminal work of De Vore and Lucier (1992) and Donoho and Johnstone (1995), new techniques for choosing appropriate threshold and/or shrinkage functions have rec ..."
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Cited by 6 (0 self)
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recently been explored by Bayesian and likelihood methods. This work is motivated by a Bayesian approach and is based on the complex representation of signals by the Symmetric Daubechies Wavelets. Applications for two dimensional signals are discussed.
Results 1  10
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