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Image inpainting algorithm based on TV model and evolutionary algorithm

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Abstract

With the development of modern image processing techniques, the numbers of images increase at a high speed in network. As a new form of visual communication, image is widely used in network transmission. However, the image information would be lost after transmission. In view of this, we are motivated to restore the image to make it complete in an effective and efficient way in order to save the network bandwidth. At present, there are two main methods for digital image restoration, texture-based method and non-textured-based method. In the texture-based method, Criminisi algorithm is a widely used algorithm. However, the inaccurate completion order and the inefficiency in searching matching patches are two main limitations of Criminisi algorithm. To overcome these shortcomings, in this paper, an exemplar image completion based on evolutionary algorithm is proposed. In the non-textured-based method, total variation method is a typical algorithm. An improved total variation algorithm is proposed in this paper. In the improved algorithm, the diffusion coefficients are defined according to the distance and direction between the damaged pixel and its neighborhood pixel. Experimental results show that the proposed algorithms have better general performance in image completion. And these two new algorithms could improve the experience of network surfing and reduce the network communication cost.

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Acknowledgments

This work is supported by the Guangdong Province Science and Technology Research Project with the Grant No. 2012A020602037 and the Research Project of Science and Technology of Education Department of Jiangxi Province of China with the Grant No. GJJ12348.

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Authors and Affiliations

  1. College of Information, South China Agricultural University, Guangzhou, 510642, China

    Kangshun Li & Wenhua Wei

  2. School of Information Science and Technology, Sun Yat-sen University, Guangzhou, Guangdong, 510006, China

    Yunshan Wei

  3. School of Information Engineering, Jiangxi University of Science and Technology, Ganzhou, 341000, China

    Zhen Yang

Authors
  1. Kangshun Li
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  2. Yunshan Wei
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  3. Zhen Yang
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  4. Wenhua Wei
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Corresponding author

Correspondence to Kangshun Li.

Additional information

Communicated by V. Loia.

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Li, K., Wei, Y., Yang, Z. et al. Image inpainting algorithm based on TV model and evolutionary algorithm. Soft Comput 20, 885–893 (2016). https://doi.org/10.1007/s00500-014-1547-7

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  • DOI: https://doi.org/10.1007/s00500-014-1547-7

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