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ECCV
2008
Springer
14 years 6 months ago
Compressive Sensing for Background Subtraction
Abstract. Compressive sensing (CS) is an emerging field that provides a framework for image recovery using sub-Nyquist sampling rates. The CS theory shows that a signal can be reco...
Volkan Cevher, Aswin C. Sankaranarayanan, Marco F....
JMIV
2002
126views more  JMIV 2002»
13 years 4 months ago
Tree-Structured Haar Transforms
In our recent work, a class of parametric transforms, including family of Haar-like transforms, was introduced and studied in application to image compression. Parametric Haar-lik...
Karen O. Egiazarian, Jaakko Astola
COMPUTING
2007
122views more  COMPUTING 2007»
13 years 4 months ago
Error estimation for Bregman iterations and inverse scale space methods in image restoration
In this paper we consider error estimation for image restoration problems based on generalized Bregman distances. This error estimation technique has been used to derive convergen...
Martin Burger, E. Resmerita, Lin He
CORR
2011
Springer
282views Education» more  CORR 2011»
12 years 11 months ago
Fast Linearized Bregman Iteration for Compressive Sensing and Sparse Denoising
We propose and analyze an extremely fast, efficient and simple method for solving the problem: min{ u 1 :Au=f,u∈Rn }. This method was first described in [1], with more details i...
Stanley Osher, Yu Mao, Bin Dong, Wotao Yin
VLSID
2004
IEEE
209views VLSI» more  VLSID 2004»
14 years 5 months ago
An Architecture for Motion Estimation in the Transform Domain
demanding algorithm of a video encoder. It is known that about 60% ~ 80% of the total computation time is consumed for motion estimation [1]. The second is its high impact on the v...
J. Lee, Narayanan Vijaykrishnan, Mary Jane Irwin, ...