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» Sparse orthonormal transforms for image compression
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CVPR
2008
IEEE
14 years 8 months ago
An efficient algorithm for compressed MR imaging using total variation and wavelets
Compressed sensing, an emerging multidisciplinary field involving mathematics, probability, optimization, and signal processing, focuses on reconstructing an unknown signal from a...
Shiqian Ma, Wotao Yin, Yin Zhang, Amit Chakraborty
ICIP
2005
IEEE
14 years 7 months ago
A nonlinear loop filter for quantization noise removal in hybrid video compression
We propose a high-performance, nonlinear, loop filter that reduces quantization noise over video frames composed of locally uniform regions (smooth, high frequency, texture, etc.)...
Onur G. Guleryuz
ICIP
2007
IEEE
14 years 8 months ago
Compressed Sensing Image Reconstruction Via Recursive Spatially Adaptive Filtering
We introduce a new approach to image reconstruction from highly incomplete data. The available data are assumed to be a small collection of spectral coef?cients of an arbitrary li...
Karen O. Egiazarian, Alessandro Foi, Vladimir Katk...
ICASSP
2011
IEEE
12 years 10 months 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
2011
IEEE
12 years 10 months ago
Image prediction based on non-negative matrix factorization
This paper presents a novel spatial texture prediction method based on non-negative matrix factorization. As an extension of template matching, approximation based iterative textu...
Mehmet Türkan, Christine Guillemot