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438
FrequencyShiftInvariant Orthonormal Wavelet Packet Representations
"... It is commonly known that wavelet expansions are very sensitive to translation of an input signal due to their dyadic structure. Without proper time alignment of the signal to the decomposition basis vectors, a compact expansion may be unattainable. Recently, work has been done to combat translation ..."
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Cited by 3 (0 self)
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translation sensitivity by determining the best translationinvariant expansion of a signal with respect to a set of bases. However, the dyadic structure of wavelet expansions also results in frequency alignment sensitivity. In this work, we introduce a frequencyshifted wavelet packet library as well
Orthonormal ShiftInvariant Wavelet Packet Decomposition and Representation
 Signal Processing
, 1995
"... In this work, a shifted wavelet packet (SWP) library, containing all the time shifted wavelet packet bases, is defined. A corresponding shiftinvariant wavelet packet decomposition (SIWPD) search algorithm for a "best basis" is introduced. The search algorithm is representable by a binar ..."
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Cited by 32 (8 self)
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In this work, a shifted wavelet packet (SWP) library, containing all the time shifted wavelet packet bases, is defined. A corresponding shiftinvariant wavelet packet decomposition (SIWPD) search algorithm for a "best basis" is introduced. The search algorithm is representable by a
A theory for multiresolution signal decomposition : the wavelet representation
 IEEE Transaction on Pattern Analysis and Machine Intelligence
, 1989
"... AbstractMultiresolution representations are very effective for analyzing the information content of images. We study the properties of the operator which approximates a signal at a given resolution. We show that the difference of information between the approximation of a signal at the resolutions ..."
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Cited by 3538 (12 self)
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2 ’ + ’ and 2jcan be extracted by decomposing this signal on a wavelet orthonormal basis of L*(R”). In LL(R), a wavelet orthonormal basis is a family of functions ( @ w (2’ ~n)),,,“jEZt, which is built by dilating and translating a unique function t+r (xl. This decomposition defines an orthogonal
Image Representation Using 2D Gabor Wavelets
 IEEE Trans. Pattern Analysis and Machine Intelligence
, 1996
"... This paper extends to two dimensions the frame criterion developed by Daubechies for onedimensional wavelets, and it computes the frame bounds for the particular case of 2D Gabor wavelets. Completeness criteria for 2D Gabor image representations are important because of their increasing role in man ..."
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Cited by 375 (4 self)
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This paper extends to two dimensions the frame criterion developed by Daubechies for onedimensional wavelets, and it computes the frame bounds for the particular case of 2D Gabor wavelets. Completeness criteria for 2D Gabor image representations are important because of their increasing role
Shift Invariant Wavelet Packet Bases
 Proc. of the 20th IEEE Int. Conf. on Acoustics, Speech and Signal Processing
, 1995
"... In this work, a shifted wavelet packet (SWP) library, con taining all the time shifted wavelet packet bases, is defined. A corresponding shiftinvariant wavelet packet decomposi tion (SIWPD) search algorithm for a "best basis" is intro duced. The search algorithm is representable by a b ..."
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Cited by 18 (8 self)
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In this work, a shifted wavelet packet (SWP) library, con taining all the time shifted wavelet packet bases, is defined. A corresponding shiftinvariant wavelet packet decomposi tion (SIWPD) search algorithm for a "best basis" is intro duced. The search algorithm is representable by a
Time Invariant Orthonormal Wavelet Representations
"... A simple construction of an orthonormal basis starting with a so called mother wavelet, together with an efficient implementation gained the wavelet decomposition easy acceptance and generated a great research interest in its applications. An orthonormal basis may not, however, always be a suitable ..."
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Cited by 71 (9 self)
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representation of a signal, particularly when time (or space) invariance is a required property. The conventional way around this problem is to use a redundant decomposition. In this paper, we address the time invariance problem for orthonormal wavelet transforms and propose an extension to wavelet packet
Shift Invariant Wavelet Packet Bases
 Proc. of the 20th IEEE Int. Conf. on Acoustics, Speech and Signal Processing
, 1995
"... In this work, a shifted wavelet packet (SWP) library, containing all the time shifted wavelet packet bases, is defined. A corresponding shiftinvariant wavelet packet decomposition (SIWPD) search algorithm for a "best basis" is introduced. The search algorithm is representable by a binary ..."
Abstract
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In this work, a shifted wavelet packet (SWP) library, containing all the time shifted wavelet packet bases, is defined. A corresponding shiftinvariant wavelet packet decomposition (SIWPD) search algorithm for a "best basis" is introduced. The search algorithm is representable by a binary
Multifrequency channel decompositions of images and wavelet models
 IEE Transactions on Acoustics, Speech And Signal Processing
, 1989
"... AbstractIn this paper we review recent multichannel models developed in psychophysiology, computer vision, and image processing. In psychophysiology, multichannel models have been particularly successful in explaining some lowlevel processing in the visual cortex. The expansion of a function int ..."
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Cited by 344 (0 self)
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into several frequency channels provides a representation which is intermediate between a spatial and a Fourier representation. We describe the mathematical properties of such decompositions and introduce the wavelet transform. We review the classical multiresolution pyramidal transforms developed
Texture classification by wavelet packet signatures
 IEEE Transaction PAMI
, 1993
"... This paper introduces a new approach tocharacterize textures at multiple scales. The performance of wavelet packet spaces are measured in terms of sensitivity and selectivity for the classi cation of twenty ve natural textures. Both energy and entropy metrics were computed for each wavelet packet a ..."
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Cited by 210 (3 self)
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and incorporated into distinct scale space representations, where each wavelet packet (channel) re ected a speci c scale and orientation sensitivity. Wavelet packet representations for twenty ve natural textures were classi ed without error by a simple twolayer network classi er. An analyzing function of large
Sampling—50 years after Shannon
 Proceedings of the IEEE
, 2000
"... This paper presents an account of the current state of sampling, 50 years after Shannon’s formulation of the sampling theorem. The emphasis is on regular sampling, where the grid is uniform. This topic has benefited from a strong research revival during the past few years, thanks in part to the math ..."
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Cited by 339 (27 self)
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of functions in the more general class of “shiftinvariant” functions spaces, including splines and wavelets. Practically, this allows for simpler—and possibly more realistic—interpolation models, which can be used in conjunction with a much wider class of (antialiasing) prefilters that are not necessarily
Results 1  10
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