TY - JOUR
T1 - A Primal-Dual Hybrid Gradient Algorithm to Solve the LLT Model for Image Denoising
AU - Chunxiao Liu, Dexing Kong & Shengfeng Zhu
JO - Numerical Mathematics: Theory, Methods and Applications
VL - 2
SP - 260
EP - 277
PY - 2012
DA - 2012/05
SN - 5
DO - http://doi.org/10.4208/nmtma.2012.m1047
UR - https://global-sci.org/intro/article_detail/nmtma/5938.html
KW - LLT model, image denoising, primal-dual.
AB - <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>