#### Filter Results:

- Full text PDF available (85)

#### Publication Year

1989

2017

- This year (3)
- Last 5 years (37)
- Last 10 years (55)

#### Publication Type

#### Co-author

#### Journals and Conferences

#### Data Set Used

#### Key Phrases

Learn More

- Stéphane Mallat
- 1999

Bargaining with reading habit is no need. Reading is not kind of something sold that you can take or not. It is a thing that will change your life to life better. It is the thing that will give you many things around the world and this universe, in the real world and here after. As what will be given by this a wavelet tour of signal processing 2nd edition,… (More)

- Stéphane Mallat
- IEEE Trans. Pattern Anal. Mach. Intell.
- 1989

It is now well admitted in the computer vision literature that a multi-resolution decomposition provides a useful image representation for vision algorithms. In this paper we show that the wavelet theory recently developed by the mathematician Y. Meyer enables us to understand and model the concepts of resolution and scale. In computer vision we generally… (More)

- Stéphane Mallat, Zhifeng Zhang
- IEEE Trans. Signal Processing
- 1993

We introduce an algorithm, called matching pursuit, that decomposes any signal into a linear expansion of waveforms that are selected from a redundant dictionary of functions. These waveforms are chosen in order to best match the signal structures. Matching pursuits are general procedures to compute adaptive signal representations. With a dictionary of… (More)

- Stéphane Mallat, Sifen Zhong
- IEEE Trans. Pattern Anal. Mach. Intell.
- 1992

A multiscale Canny edge detection is equivalent to finding the local maxima of a wavelet transform. We study the properties of multiscale edges through the wavelet theory. For pattern recognition, one often needs to discriminate different types of edges. We show that the evolution of wavelet local maxima across scales characterize the local shape of… (More)

- Stéphane Mallat, Wen Liang Hwang
- IEEE Trans. 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 wavelet transform are explained. We then prove that the local… (More)

A multiresolution approximation is a sequence of embedded vector spaces Vj jmember Z for approximating L 2 (R) functions. We study the properties of a multiresolution approximation and prove that it is characterized by a 2π periodic function which is further described. From any multiresolution approximation, we can derive a function ψ(x ) called a… (More)

- Stéphane Mallat
- IEEE Trans. Acoustics, Speech, and Signal…
- 1989

In 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 low-level processing in the visual cortex. The expansion of a function into several frequency channels provides a representation which is… (More)

- Joan Bruna, Stéphane Mallat
- IEEE Transactions on Pattern Analysis and Machine…
- 2013

A wavelet scattering network computes a translation invariant image representation which is stable to deformations and preserves high-frequency information for classification. It cascades wavelet transform convolutions with nonlinear modulus and averaging operators. The first network layer outputs SIFT-type descriptors, whereas the next layers provide… (More)

- Stéphane Mallat
- ArXiv
- 2011

This paper constructs translation invariant operators on L(Rd), which are Lipschitz continuous to the action of diffeomorphisms. A scattering propagator is a path ordered product of non-linear and non-commuting operators, each of which computes the modulus of a wavelet transform. A local integration defines a windowed scattering transform, which is proved… (More)

- Guoshen Yu, Guillermo Sapiro, Stéphane Mallat
- IEEE Transactions on Image Processing
- 2012

A general framework for solving image inverse problems with piecewise linear estimations is introduced in this paper. The approach is based on Gaussian mixture models, which are estimated via a maximum a posteriori expectation-maximization algorithm. A dual mathematical interpretation of the proposed framework with a structured sparse estimation is… (More)