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» Learning denoising bounds for noisy images
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ICASSP
2011
IEEE
12 years 9 months ago
Denoising of image patches via sparse representations with learned statistical dependencies
We address the problem of denoising for image patches. The approach taken is based on Bayesian modeling of sparse representations, which takes into account dependencies between th...
Tomer Faktor, Yonina C. Eldar, Michael Elad
ICIP
2010
IEEE
13 years 3 months ago
Exemplar-Based EM-like image denoising via manifold reconstruction
Discovering local geometry of low-dimensional manifold embedded into a high-dimensional space has been widely studied in the literature of machine learning. Counter-intuitively, w...
Xin Li
PAMI
2008
181views more  PAMI 2008»
13 years 5 months ago
Automatic Estimation and Removal of Noise from a Single Image
Image denoising algorithms often assume an additive white Gaussian noise (AWGN) process that is independent of the actual RGB values. Such approaches cannot effectively remove colo...
Ce Liu, Richard Szeliski, Sing Bing Kang, C. Lawre...
MP
2010
162views more  MP 2010»
13 years 3 months ago
Approximation accuracy, gradient methods, and error bound for structured convex optimization
Convex optimization problems arising in applications, possibly as approximations of intractable problems, are often structured and large scale. When the data are noisy, it is of i...
Paul Tseng
CCIW
2011
Springer
12 years 8 months ago
On the Application of Structured Sparse Model Selection to JPEG Compressed Images
The representation model that considers an image as a sparse linear combination of few atoms of a predefined or learned dictionary has received considerable attention in recent ye...
Giovanni Maria Farinella, Sebastiano Battiato