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Hybrid Variational Model for Texture Image Restoration

Published online by Cambridge University Press:  07 September 2017

Liyan Ma*
Affiliation:
Institute of Microelectronics of Chinese Academy of Sciences, Beijing, China
Tieyong Zeng*
Affiliation:
Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China HKBU Institute of Research and Continuing Education, Shenzhen Virtual University Park, Shenzhen 518057, China
Gongyan Li*
Affiliation:
Institute of Microelectronics of Chinese Academy of Sciences, Beijing, China
*
*Corresponding author. Email addresses:maliyan@ime.ac.cn (L. Ma), zeng@hkbu.edu.hk (T. Zeng), ligongyan@ime.ac.cn (G. Li)
*Corresponding author. Email addresses:maliyan@ime.ac.cn (L. Ma), zeng@hkbu.edu.hk (T. Zeng), ligongyan@ime.ac.cn (G. Li)
*Corresponding author. Email addresses:maliyan@ime.ac.cn (L. Ma), zeng@hkbu.edu.hk (T. Zeng), ligongyan@ime.ac.cn (G. Li)
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Abstract

The hybrid variational model for restoration of texture images corrupted by blur and Gaussian noise we consider combines total variation regularisation and a fractional-order regularisation, and is solved by an alternating minimisation direction algorithm. Numerical experiments demonstrate the advantage of this model over the adaptive fractional-order variational model in image quality and computational time.

Type
Research Article
Copyright
Copyright © Global-Science Press 2017 

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