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» On Sparsity and Overcompleteness in Image Models
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JMIV
2011
138views more  JMIV 2011»
13 years 2 months ago
Direct Sparse Deblurring
We propose a deblurring algorithm that explicitly takes into account the sparse characteristics of natural images and does not entail solving a numerically ill-conditioned backwar...
Yifei Lou, Andrea L. Bertozzi, Stefano Soatto
CVPR
2011
IEEE
13 years 5 months ago
Sparsity-based Image Denoising via Dictionary Learning and Structural Clustering
Where does the sparsity in image signals come from? Local and nonlocal image models have supplied complementary views toward the regularity in natural images the former attempts t...
Weisheng Dong, Xin Li
ICIP
1998
IEEE
14 years 1 days ago
Spatially Adaptive Wavelet Thresholding with Context Modeling for Image Denoising
The method of wavelet thresholding for removing noise, or denoising, has been researched extensively due to its effectiveness and simplicity. Much of the literature has focused on ...
S. Grace Chang, Bin Yu, Martin Vetterli
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
IDA
2009
Springer
14 years 2 months ago
Learning Natural Image Structure with a Horizontal Product Model
We present a novel extension to Independent Component Analysis (ICA), where the data is generated as the product of two submodels, each of which follow an ICA model, and which comb...
Urs Köster, Jussi T. Lindgren, Michael Gutman...