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International Conference on Knowledge Science, Engineering and Management

KSEM 2017: Knowledge Science, Engineering and Management pp 458–465Cite as

A Weighted Non-monotonic Averaging Image Reduction Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10412))

Abstract

Image reduction is commonly used as a data pre-processing method in many image processing field, an efficient image reduction operator can underpinning many practical applications. Traditional monotonic averaging image reduction operator may lost some detail features during reduction. However, In certain task those small features have very important significance. Therefore, some scholars proposed a non-monotonic averaging image reduction algorithm, recent works focus on integrate the pixel cluster’s space structure information into image representative pixel selection progress, it has certain practical significance but this method is only suitable for specific background pictures. To fill this gap, We propose an novel sigmoid function based weighted image reduction algorithm, which can be used to image reduction under different background colours. Experiments show that the proposed method has better image reduction effect on images with different background colors.

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Acknowledgments

The authors would like to thank the anonymous reviewers for their constructive comments. This research is supported by the International Cooperation and Exchanges in Science and Technology Plan Project in Shannxi under the Grant No. 2016kw-047.

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Authors and Affiliations

  1. School of Computer Science, Xi’an ShiYou University, Shaanxi, 710065, China

    Jiaxin Han & Haiyang Xia

Authors
  1. Jiaxin Han
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  2. Haiyang Xia
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Corresponding author

Correspondence to Haiyang Xia .

Editor information

Editors and Affiliations

  1. Deakin University, Burwood, Victoria, Australia

    Gang Li

  2. University of Arizona, Tucson, Arizona, USA

    Yong Ge

  3. Southwest University, Chongqing, China

    Zili Zhang

  4. Peking University, Beijing, China

    Zhi Jin

  5. University of Technology Sydney, Sydney, New South Wales, Australia

    Michael Blumenstein

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Han, J., Xia, H. (2017). A Weighted Non-monotonic Averaging Image Reduction Algorithm. In: Li, G., Ge, Y., Zhang, Z., Jin, Z., Blumenstein, M. (eds) Knowledge Science, Engineering and Management. KSEM 2017. Lecture Notes in Computer Science(), vol 10412. Springer, Cham. https://doi.org/10.1007/978-3-319-63558-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-63558-3_39

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-63557-6

  • Online ISBN: 978-3-319-63558-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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