Numerical Methods for Non-Smooth L1 Optimization: Applications to Free Surface Flows and Image Denoising
Year: 2009
International Journal of Numerical Analysis and Modeling, Vol. 6 (2009), Iss. 3 : pp. 355–374
Abstract
Non-smooth optimization problems based on L1 norms are investigated for smoothing of signals with noise or functions with sharp gradients. The use of L1 norms allows to reduce the blurring introduced by methods based on L2 norms. Numerical methods based on over-relaxation and augmented Lagrangian algorithms are proposed. Applications to free surface flows and image denoising are presented.
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Journal Article Details
Publisher Name: Global Science Press
Language: English
DOI: https://doi.org/2009-IJNAM-772
International Journal of Numerical Analysis and Modeling, Vol. 6 (2009), Iss. 3 : pp. 355–374
Published online: 2009-01
AMS Subject Headings: Global Science Press
Copyright: COPYRIGHT: © Global Science Press
Pages: 20
Keywords: L1 optimization over-relaxation algorithm augmented Lagrangian methods smoothing image denoising.