A splitting algorithm for directional regularization and sparsification

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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.
Original languageEnglish
Title of host publicationProceedings of the 21st International Conference on Pattern Recognition (ICPR)
Number of pages5
PublisherIEEE
Publication date2012
Pages3094-3098
ISBN (Print)978-4-9906441-0-9
Publication statusPublished - 2012
EventInternational Conference on Pattern Recognition - Tsukuba International Congress Center, Tsukuba, Japan
Duration: 11 Nov 201215 Nov 2012
Conference number: 21

Conference

ConferenceInternational Conference on Pattern Recognition
Nummer21
LocationTsukuba International Congress Center
LandJapan
ByTsukuba
Periode11/11/201215/11/2012

ID: 38468530