@Article{NMTMA-5-260,
author = {Chunxiao Liu, Dexing Kong and Shengfeng Zhu},
title = {A Primal-Dual Hybrid Gradient Algorithm to Solve the LLT Model for Image Denoising},
journal = {Numerical Mathematics: Theory, Methods and Applications},
year = {2012},
volume = {5},
number = {2},
pages = {260--277},
abstract = {<p style="text-align: justify;">We propose an efficient gradient-type algorithm to solve the fourth-order LLT denoising model for both gray-scale and
vector-valued images. Based on the primal-dual formulation of the
original nondifferentiable model, the new algorithm updates the
primal and dual variables alternately using the gradient
descent/ascent flows. Numerical examples are provided to demonstrate
the superiority of our algorithm.</p>},
issn = {2079-7338},
doi = {https://doi.org/10.4208/nmtma.2012.m1047},
url = {http://global-sci.org/intro/article_detail/nmtma/5938.html}
}