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An automatic video scratch removal based on Thiele type continued fraction

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Abstract

Old age, repeat play and improper preservation always deteriorate the film, and dust and mechanical operations produce artifacts like scratches and blotches. Many researches carried out to repair the damaged digital videos and video inpainting gradually becomes an important topic in digital image process ing. Challenges in scratched video inpainting are automatic detection of scratches and restoration of damaged part. This paper presents an automatic scratch detec tion method as well as a novel scratch removal approach. Stationary wavelet transform (SWT) which shows excellent performance in keeping translation-invariant is introduced to automatically detect the scratches, this strategy makes the scratches’ detection more accurate. At the heart of our method is a new nonlinear interpolation method based on continued fraction in which Thiele-type continued fraction is used to interpolate surrounding known pixels for repairing the damaged part. Algorithm presented in this paper also utilizes both spatial and temporal information of the scratched video during the restoration stage. Experimental results show that our scheme not only obtains more accurate detection of scratches, but also gives better video quality.

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Abbreviations

PDE:

Partial differential equation

TV:

Total variation

CCD:

Curvature-driven diffusion

OWE:

Over-complete wavelet expansion

SWT:

Stationary wavelet transform

GBMCI:

Global bi-directional motion compensation frame interpolation

MV:

Motion vectors

CF:

Continued fraction

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Acknowledgments

The authors would like to thank Prelinger Archives (http://www.archive.org) for archive film material. We sincerely appreciate the financial support of National Natural Science Foundation of China and we are also grateful to editor and reviewers for their constructive comments and suggestions.

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Authors and Affiliations

  1. School of Computer and Information, School of Mathematics, Hefei University of Technology, Hefei, Anhui, People’s Republic of China

    Xing Huo, Jieqing Tan & Lei He

  2. School of Computer and Information, Hefei University of Technology, Hefei, Anhui, People’s Republic of China

    Min Hu

Authors
  1. Xing Huo
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  2. Jieqing Tan
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  3. Lei He
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  4. Min Hu
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Corresponding author

Correspondence to Xing Huo.

Additional information

This work was supported by the NSFC–Guangdong Joint Foundation Key Project (Grant No. U1135003), the National Natural Science Foundation of China (Grant No. 61070227, 60773043), and the Foundation for Key Program of Ministry of Education of China (No. 309017).

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Huo, X., Tan, J., He, L. et al. An automatic video scratch removal based on Thiele type continued fraction. Multimed Tools Appl 71, 451–467 (2014). https://doi.org/10.1007/s11042-013-1523-8

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