Results 1 - 10 of 29,125

Factoring wavelet transforms into lifting steps

by Ingrid Daubechies, Wim Sweldens - J. FOURIER ANAL. APPL , 1998
"... This paper is essentially tutorial in nature. We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed into a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures. This decompositio ..."
Abstract - Cited by 584 (8 self) - Add to MetaCart
This paper is essentially tutorial in nature. We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed into a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures

Singularity Detection And Processing With Wavelets

by Stephane Mallat, Wen Liang Hwang - IEEE Transactions on Information Theory , 1992
"... Most of a signal information is often found in irregular structures and transient phenomena. We review the mathematical characterization of singularities with Lipschitz exponents. The main theorems that estimate local Lipschitz exponents of functions, from the evolution across scales of their wavele ..."
Abstract - Cited by 595 (13 self) - Add to MetaCart
of their wavelet transform are explained. We then prove that the local maxima of a wavelet transform detect the location of irregular structures and provide numerical procedures to compute their Lipschitz exponents. The wavelet transform of singularities with fast oscillations have a different behavior that we

A Practical Guide to Wavelet Analysis

by Christopher Torrence, Gilbert P. Compo , 1998
"... A practical step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nio-- Southern Oscillation (ENSO). The guide includes a comparison to the windowed Fourier transform, the choice of an appropriate wavelet basis function, edge effects due to finite-length t ..."
Abstract - Cited by 869 (3 self) - Add to MetaCart
A practical step-by-step guide to wavelet analysis is given, with examples taken from time series of the El Nio-- Southern Oscillation (ENSO). The guide includes a comparison to the windowed Fourier transform, the choice of an appropriate wavelet basis function, edge effects due to finite

The Lifting Scheme: A Construction Of Second Generation Wavelets

by Wim Sweldens , 1997
"... We present the lifting scheme, a simple construction of second generation wavelets, wavelets that are not necessarily translates and dilates of one fixed function. Such wavelets can be adapted to intervals, domains, surfaces, weights, and irregular samples. We show how the lifting scheme leads to a ..."
Abstract - Cited by 539 (15 self) - Add to MetaCart
to a faster, in-place calculation of the wavelet transform. Several examples are included.

A theory for multiresolution signal decomposition : the wavelet representation

by G. Mallat - IEEE Transaction on Pattern Analysis and Machine Intelligence , 1989
"... Abstract-Multiresolution 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 ..."
Abstract - Cited by 3538 (12 self) - Add to MetaCart
in image coding, texture discrimination and fractal analysis. Index Terms-Coding, fractals, multiresolution pyramids, quadrature mirror filters, texture discrimination, wavelet transform. I I.

Shiftable Multi-scale Transforms

by Eero Simoncelli, William T. Freeman, Edward H. Adelson, David J. Heeger , 1992
"... Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal. Wavel ..."
Abstract - Cited by 562 (36 self) - Add to MetaCart
Orthogonal wavelet transforms have recently become a popular representation for multiscale signal and image analysis. One of the major drawbacks of these representations is their lack of translation invariance: the content of wavelet subbands is unstable under translations of the input signal

An affine invariant interest point detector

by Krystian Mikolajczyk, Cordelia Schmid - In Proceedings of the 7th European Conference on Computer Vision , 2002
"... Abstract. This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such transformations introduce significant changes in the point location as well as in the scale and the shape of ..."
Abstract - Cited by 1467 (55 self) - Add to MetaCart
Abstract. This paper presents a novel approach for detecting affine invariant interest points. Our method can deal with significant affine transformations including large scale changes. Such transformations introduce significant changes in the point location as well as in the scale and the shape

The Contourlet Transform: An Efficient Directional Multiresolution Image Representation

by Minh N. Do, Martin Vetterli - IEEE TRANSACTIONS ON IMAGE PROCESSING
"... The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” two-dimensional transform that can capture the intrinsic geometrical structure t ..."
Abstract - Cited by 513 (20 self) - Add to MetaCart
The limitations of commonly used separable extensions of one-dimensional transforms, such as the Fourier and wavelet transforms, in capturing the geometry of image edges are well known. In this paper, we pursue a “true” two-dimensional transform that can capture the intrinsic geometrical structure

Fast and robust fixed-point algorithms for independent component analysis

by Aapo Hyvärinen - IEEE TRANS. NEURAL NETW , 1999
"... Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s informat ..."
Abstract - Cited by 884 (34 self) - Add to MetaCart
Independent component analysis (ICA) is a statistical method for transforming an observed multidimensional random vector into components that are statistically as independent from each other as possible. In this paper, we use a combination of two different approaches for linear ICA: Comon’s

Interior Point Methods in Semidefinite Programming with Applications to Combinatorial Optimization

by Farid Alizadeh - SIAM Journal on Optimization , 1993
"... We study the semidefinite programming problem (SDP), i.e the problem of optimization of a linear function of a symmetric matrix subject to linear equality constraints and the additional condition that the matrix be positive semidefinite. First we review the classical cone duality as specialized to S ..."
Abstract - Cited by 547 (12 self) - Add to MetaCart
to SDP. Next we present an interior point algorithm which converges to the optimal solution in polynomial time. The approach is a direct extension of Ye's projective method for linear programming. We also argue that most known interior point methods for linear programs can be transformed in a
Results 1 - 10 of 29,125