TY - JOUR
T1 - A Semi-Implicit Binary Level Set Method for Source Reconstruction Problems
AU - C. Liu & S. Zhu
JO - International Journal of Numerical Analysis and Modeling
VL - 3
SP - 410
EP - 426
PY - 2011
DA - 2011/08
SN - 8
DO - http://doi.org/
UR - https://global-sci.org/intro/article_detail/ijnam/693.html
KW - source reconstruction, binary level set method, augmented Lagrangian method, additive operator splitting.
AB - <p style="text-align: justify;">The aim of this paper is to investigate the application of a semi-implicit additive operator splitting scheme based binary level set method to
source reconstruction problems. We reformulate the original model to be a
new constrained optimization problem under the binary level set framework and
solve it by the augmented Lagrangian method. Then we propose an efficient
gradient-type algorithm based on the additive operator splitting scheme. The
proposed algorithm can create new holes during the evolution. Topological
changes can be handled automatically and complex geometry can be recovered
under a certain amount of noise in the observation data. Numerical examples
are presented to show the effectiveness and efficiency of our method.</p>