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A Primal-Dual Hybrid Gradient Algorithm to Solve the LLT Model for Image Denoising

Published online by Cambridge University Press:  28 May 2015

Chunxiao Liu ,
Dexing Kong  and
Shengfeng Zhu
Chunxiao Liu*
Affiliation:
Department of Mathematics, Hangzhou Normal University, Hangzhou 310036, China
Dexing Kong*
Affiliation:
Department of Mathematics, Zhejiang University, Hangzhou, China
Shengfeng Zhu*
Affiliation:
Department of Mathematics, Zhejiang University, Hangzhou, China
*
Corresponding author.Email address:xxliul98431@126.com
Corresponding author.Email address:kong@cms.zju.edu.cn
Corresponding author.Email address:shengfengzhu@zju.edu.cn
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Abstract

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.

Keywords

68U1065K10LLT modelimage denoisingprimal-dual
Type
Research Article
Information
Numerical Mathematics: Theory, Methods and Applications , Volume 5 , Issue 2 , May 2012 , pp. 260 - 277
Copyright
Copyright © Global Science Press Limited 2012

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