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» Learning Overcomplete Representations
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ICCV
2003
IEEE
14 years 1 months ago
Modeling Textured Motion : Particle, Wave and Sketch
In this paper, we present a generative model for textured motion phenomena, such as falling snow, wavy river and dancing grass, etc. Firstly, we represent an image as a linear sup...
Yizhou Wang, Song Chun Zhu
TASLP
2010
138views more  TASLP 2010»
13 years 3 months ago
Glimpsing IVA: A Framework for Overcomplete/Complete/Undercomplete Convolutive Source Separation
Abstract--Independent vector analysis (IVA) is a method for separating convolutedly mixed signals that significantly reduces the occurrence of the well-known permutation problem in...
Alireza Masnadi-Shirazi, Wenyi Zhang, Bhaskar D. R...
ICASSP
2011
IEEE
13 years 9 days ago
Denoising sparse noise via online dictionary learning
The idea of learning overcomplete dictionaries based on the paradigm of compressive sensing has found numerous applications, among which image denoising is considered one of the m...
Anoop Cherian, Suvrit Sra, Nikolaos Papanikolopoul...
ICASSP
2008
IEEE
14 years 3 months ago
A first step to convolutive sparse representation
In this paper an extension of the sparse decomposition problem is considered and an algorithm for solving it is presented. In this extension, it is known that one of the shifted v...
Hamed Firouzi, Massoud Babaie-Zadeh, Aria Ghasemia...
ICIP
2001
IEEE
14 years 10 months ago
On sparse signal representations
An elementary proof of a basic uncertainty principle concerning pairs of representations of ?? vectors in different orthonormal bases is provided. The result, slightly stronger th...
Michael Elad, Alfred M. Bruckstein