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 -