Implementation of an optimal first-order method for strongly convex total variation regularization
نویسندگان
چکیده
منابع مشابه
Implementation of an Optimal First-Order Method for Strongly Convex Total Variation Regularization
We present a practical implementation of an optimal first-order method, due to Nesterov, for large-scale total variation regularization in tomographic reconstruction, image deblurring, etc. The algorithm applies to μ-strongly convex objective functions with L-Lipschitz continuous gradient. In the framework of Nesterov both μ and L are assumed known – an assumption that is seldom satisfied in pr...
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ژورنال
عنوان ژورنال: BIT Numerical Mathematics
سال: 2011
ISSN: 0006-3835,1572-9125
DOI: 10.1007/s10543-011-0359-8