@Article{EAJAM-11-2,
author = {Zhang, Yinghui and Xiaojuan, Deng and Zhao, Xing and Li, Hongwei},
title = {A Restricted Linearised Augmented Lagrangian Method for Euler's Elastica Model},
journal = {East Asian Journal on Applied Mathematics},
year = {2021},
volume = {11},
number = {2},
pages = {276--300},
abstract = {<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>},
issn = {2079-7370},
doi = {https://doi.org/10.4208/eajam.200520.191020},
url = {https://global-sci.com/article/82503/a-restricted-linearised-augmented-lagrangian-method-for-eulers-elastica-model}
}