TY - JOUR
T1 - A Restricted Linearised Augmented Lagrangian Method for Euler's Elastica Model
AU - Zhang , Yinghui
AU - Deng , Xiaojuan
AU - Zhao , Xing
AU - Li , Hongwei
JO - East Asian Journal on Applied Mathematics
VL - 2
SP - 276
EP - 300
PY - 2021
DA - 2021/02
SN - 11
DO - http://doi.org/10.4208/eajam.200520.191020
UR - https://global-sci.org/intro/article_detail/eajam/18635.html
KW - Euler's elastica, augmented Lagrangian, image denoising.
AB - <p style="text-align: justify;">A simple cutting-off strategy for the augmented Lagrangian formulation for
minimising the Euler&#39;s elastica energy is introduced. It is connected to a discovered
internal inconsistency of the model and helps to decouple the tricky dependence between
auxiliary splitting variables, thus fixing the problem mentioned. Numerical experiments
show that the method converges much faster than conventional algorithms, provides
a better parameter-tuning and ensures the higher quality of image restorations.</p>