Linearized Bregman iterations for compressed sensing
نویسندگان
چکیده
منابع مشابه
Linearized Bregman iterations for compressed sensing
Finding a solution of a linear equation Au = f with various minimization properties arises from many applications. One of such applications is compressed sensing, where an efficient and robust-to-noise algorithm to find a minimal `1 norm solution is needed. This means that the algorithm should be tailored for large scale and completely dense matrices A, while Au and A u can be computed by fast ...
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Real images usually have sparse approximations under some tight frame systems derived from either framelets, over sampled discrete (window) cosine or Fourier transform. In this paper, we propose a method for image deblurring in tight frame domains. It is reduced to finding a sparse solution of a system of linear equations whose coefficients matrix is rectangular. Then, a modified version of the...
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This method was first described in [J. Darbon and S. Osher, preprint, 2007], with more details in [W. Yin, S. Osher, D. Goldfarb and J. Darbon, SIAM J. Imaging Sciences, 1(1), 143-168, 2008] and rigorous theory given in [J. Cai, S. Osher and Z. Shen, Math. Comp., to appear, 2008, see also UCLA CAM Report 08-06] and [J. Cai, S. Osher and Z. Shen, UCLA CAM Report, 08-52, 2008]. The motivation was...
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ژورنال
عنوان ژورنال: Mathematics of Computation
سال: 2009
ISSN: 0025-5718,1088-6842
DOI: 10.1090/s0025-5718-08-02189-3