@Article{EAJAM-11-276, author = {Zhang , YinghuiDeng , XiaojuanZhao , 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 = {
A simple cutting-off strategy for the augmented Lagrangian formulation for minimising the Euler'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.
}, issn = {2079-7370}, doi = {https://doi.org/10.4208/eajam.200520.191020}, url = {http://global-sci.org/intro/article_detail/eajam/18635.html} }