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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
SIAMNUM
2010
120views more  SIAMNUM 2010»
13 years 1 days ago
Sparse Spectral Approximations of High-Dimensional Problems Based on Hyperbolic Cross
Hyperbolic cross approximations by some classical orthogonal polynomials/functions in both bounded and unbounded domains are considered in this paper. Optimal error estimates in pr...
Jie Shen, Li-lian Wang
TIP
2010
155views more  TIP 2010»
13 years 3 months ago
Is Denoising Dead?
—Image denoising has been a well studied problem in the field of image processing. Yet researchers continue to focus attention on it to better the current state-of-the-art. Rece...
Priyam Chatterjee, Peyman Milanfar
ICPR
2008
IEEE
13 years 11 months ago
Robust estimation of foreground in surveillance videos by sparse error estimation
Frames of videos with static background and dynamic foreground can be viewed as samples of signals that vary slowly in time with sparse corruption caused by foreground objects. We...
Mert Dikmen, Thomas S. Huang
ICIP
2010
IEEE
13 years 3 months ago
Learning denoising bounds for noisy images
In [1], we derived an expression for the fundamental limit to image denoising assuming that the noise-free image is available. In this paper, we propose an estimator for the bound...
Priyam Chatterjee, Peyman Milanfar