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- Publications
- Influence
Ten Lectures on Wavelets
- I. Daubechies, C. Heil
- Mathematics, Computer Science
- 1 May 1992
TLDR
Orthonormal bases of compactly supported wavelets
- I. Daubechies
- Mathematics
- 1 October 1988
We construct orthonormal bases of compactly supported wavelets, with arbitrarily high regularity. The order of regularity increases linearly with the support width. We start by reviewing the concept… Expand
An Iterative Thresholding Algorithm for Linear Inverse Problems with a Sparsity Constraint
- I. Daubechies, M. Defrise, C. D. Mol
- Mathematics
- 10 July 2003
We consider linear inverse problems where the solution is assumed to have a sparse expansion on an arbitrary preassigned orthonormal basis. We prove that replacing the usual quadratic regularizing… Expand
The wavelet transform, time-frequency localization and signal analysis
- I. Daubechies
- Mathematics, Computer Science
- IEEE Trans. Inf. Theory
- 1 September 1990
TLDR
Image coding using wavelet transform
- M. Antonini, M. Barlaud, P. Mathieu, I. Daubechies
- Mathematics, Computer Science
- IEEE Trans. Image Process.
- 1 April 1992
TLDR
Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool
- I. Daubechies, J. Lu, H. Wu
- Mathematics
- 1 March 2011
Abstract The EMD algorithm is a technique that aims to decompose into their building blocks functions that are the superposition of a (reasonably) small number of components, well separated in the… Expand
Factoring wavelet transforms into lifting steps
- I. Daubechies, W. Sweldens
- 1998
This article 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… Expand
Biorthogonal bases of compactly supported wavelets
- Albert Cohen, I. Daubechies, J. Feauveau
- Mathematics
- 1 June 1992
Orthonormal bases of compactly supported wavelet bases correspond to subband coding schemes with exact reconstruction in which the analysis and synthesis filters coincide. We show here that under… Expand
Iteratively reweighted least squares minimization for sparse recovery
- I. Daubechies, R. Devore, M. Fornasier, C. S. Gunturk
- Mathematics
- 3 July 2008
Under certain conditions (known as the restricted isometry property, or RIP) on the mN matrix ˆ (where m<N ), vectors x 2 R N that are sparse (i.e., have most of their entries equal to 0) can be… Expand
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