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Structure-Preserving Guided Image Filtering

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Intelligence Science and Big Data Engineering. Visual Data Engineering (IScIDE 2019)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 11935))

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Abstract

Guided filter behaves as a structure-transferring filter which takes advantage of the guidance image. Nevertheless, it is likely to suffer from structure information loss problem and artifacts would be introduced in practical tasks, e.g., detail enhancement. We in this paper propose to deal with the structure loss problem. We modify the original objective function and develop a re-weighted algorithm to proceed the filtering process iteratively. The proposed filter inherits good properties of guided filter and is more capable in avoiding structure information loss. Many vision tasks can be benefited from the proposed filter. Few applications we outline include flash/no-flash image restoration, image dehazing, detail enhancement, HDR compression, and image matting. Experimental comparisons with relative methods for these tasks demonstrate the effectiveness of the proposed filter.

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Acknowledgements

This work has been partially supported by National Natural Science Foundation of China (No. 61572099).

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Authors and Affiliations

  1. School of Mathematical Sciences, Dalian University of Technology, Dalian, 116024, China

    Hongyan Wang, Zhixun Su & Songxin Liang

Authors
  1. Hongyan Wang
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  2. Zhixun Su
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  3. Songxin Liang
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Corresponding author

Correspondence to Zhixun Su .

Editor information

Editors and Affiliations

  1. Nanjing University of Science and Technology, Nanjing, China

    Zhen Cui

  2. Nanjing University of Science and Technology, Nanjing, China

    Jinshan Pan

  3. Nanjing University of Science and Technology, Nanjing, China

    Shanshan Zhang

  4. Nanjing University of Science and Technology, Nanjing, China

    Liang Xiao

  5. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

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Wang, H., Su, Z., Liang, S. (2019). Structure-Preserving Guided Image Filtering. In: Cui, Z., Pan, J., Zhang, S., Xiao, L., Yang, J. (eds) Intelligence Science and Big Data Engineering. Visual Data Engineering. IScIDE 2019. Lecture Notes in Computer Science(), vol 11935. Springer, Cham. https://doi.org/10.1007/978-3-030-36189-1_10

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  • DOI: https://doi.org/10.1007/978-3-030-36189-1_10

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-36188-4

  • Online ISBN: 978-3-030-36189-1

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