A splitting algorithm for directional regularization and sparsification
Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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A splitting algorithm for directional regularization and sparsification. / Rakêt, Lars Lau; Nielsen, Mads.
Proceedings of the 21st International Conference on Pattern Recognition (ICPR). IEEE, 2012. s. 3094-3098.Publikation: Bidrag til bog/antologi/rapport › Konferencebidrag i proceedings › Forskning › fagfællebedømt
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TY - GEN
T1 - A splitting algorithm for directional regularization and sparsification
AU - Rakêt, Lars Lau
AU - Nielsen, Mads
N1 - Conference code: 21
PY - 2012
Y1 - 2012
N2 - We present a new split-type algorithm for the minimization of a p-harmonic energy with added data fidelity term. The half-quadratic splitting reduces the original problem to two straightforward problems, that can be minimized efficiently. The minimizers to the two sub-problems can typically be computed pointwise and are easily implemented on massively parallel processors. Furthermore the splitting method allows for the computation of solutions to a large number of more advanced directional regularization problems. In particular we are able to handle robust, non-convex data terms, and to define a 0-harmonic regularization energy where we sparsify directions by means of an L0 norm.
AB - We present a new split-type algorithm for the minimization of a p-harmonic energy with added data fidelity term. The half-quadratic splitting reduces the original problem to two straightforward problems, that can be minimized efficiently. The minimizers to the two sub-problems can typically be computed pointwise and are easily implemented on massively parallel processors. Furthermore the splitting method allows for the computation of solutions to a large number of more advanced directional regularization problems. In particular we are able to handle robust, non-convex data terms, and to define a 0-harmonic regularization energy where we sparsify directions by means of an L0 norm.
M3 - Article in proceedings
SN - 978-4-9906441-0-9
SP - 3094
EP - 3098
BT - Proceedings of the 21st International Conference on Pattern Recognition (ICPR)
PB - IEEE
Y2 - 11 November 2012 through 15 November 2012
ER -
ID: 38468530