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International Conference of Pioneering Computer Scientists, Engineers and Educators

ICYCSEE 2016: Social Computing pp 48–55Cite as

A Novel Filtering Method for Infrared Image

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Part of the book series: Communications in Computer and Information Science ((CCIS,volume 623))

Abstract

The image filtering technology is widely used in many fields, such as environmental monitoring and assessment, space remote sensing, recognition and tracking of infrared target. In this paper, aiming at the problem of poor generalization capability and over-fitting with artificial neutral network for infrared image filtering, a new filtering method is presented. The structure elements are used to set up the training samples. And then, based on support vector machine theory, it builds the learning ma-chine with proper model and trains the samples. The result can be used to suppress the background SNR of following image. The experimental result with infrared image shows that the method can obtain higher SNR than conventional neutral network and fixed Top-Hat operator method, especially in low SNR.

This research is partly supported by the innovative research fund of aerospace, research fund for the program of new century excellent talents in Heilongjiang provincial university No. 1155-ncet-008 and the National Natural Science Foundation of China under grant No. 60903083, 61502123.

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References

  1. XIE, K., XU, G., LIU, X.: Optimized design for mathematics morphology filter. Comput. Eng. Appl. 35, 103–105 (2003)

    Google Scholar 

  2. Won, Y.G., Gader, P.G., Coffield, P.D.: Morphological shared-weight networks with applications to automatic target recognition. Trans. Neural Netw. 8(5), 1195–1203 (1997)

    Article  Google Scholar 

  3. Ritter, G.X., Sussner, P., Diza-de-Leon J.L. Morphological neural networks. In: Neural Networks Proceedings IJCNN 2001 International Joint Conference, vol. 4(15), pp. 2518–2523 (2001)

    Google Scholar 

  4. Grana, M., Raducanu, B.: Some applications of morphological neural networks. In: Neural Networks Proceedings IJCNN 2001 International Joint Conference, vol. 4(15), pp. 2518–2523 (2001)

    Google Scholar 

  5. Zheng, S., LIU, J., Tian, J.: Research of SVM-based infrared small object segmentation and clustering method. Sig. Proc. 21(5), 515–519 (2005)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Beijing Institute of Astronautical Systems Engineering, Beijing, China

    Jian Kang, Chunxiao Zhou, Weiqiang Xia & Chaopeng Shen

  2. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, Heilongjiang, China

    Guanglu Sun

Authors
  1. Jian Kang
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  2. Chunxiao Zhou
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  3. Weiqiang Xia
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  4. Chaopeng Shen
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  5. Guanglu Sun
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Corresponding author

Correspondence to Jian Kang .

Editor information

Editors and Affiliations

  1. Harbin Institute of Technology , Harbin, China

    Wanxiang Che

  2. Harbin Engineering University , Harbin, China

    Qilong Han

  3. Harbin Institute of Technology , Harbin, China

    Hongzhi Wang

  4. Northeast Forestry University , Harbin, China

    Weipeng Jing

  5. National University of Defense Technology , Changsha, China

    Shaoliang Peng

  6. Harbin Engineering University , Harbin, China

    Junyu Lin

  7. Harbin Univ. of Science and Technology , Harbin, China

    Guanglu Sun

  8. Harbin Univ. of Science and Technology , Harbin, China

    Xianhua Song

  9. Harbin Engineering University , Harbin, China

    Hongtao Song

  10. Harbin Sea of Clouds & Computer Tech. , Harbin, China

    Zeguang Lu

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© 2016 Springer Science+Business Media Singapore

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Cite this paper

Kang, J., Zhou, C., Xia, W., Shen, C., Sun, G. (2016). A Novel Filtering Method for Infrared Image. In: Che, W., et al. Social Computing. ICYCSEE 2016. Communications in Computer and Information Science, vol 623. Springer, Singapore. https://doi.org/10.1007/978-981-10-2053-7_5

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  • DOI: https://doi.org/10.1007/978-981-10-2053-7_5

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-2052-0

  • Online ISBN: 978-981-10-2053-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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