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Design and Implementation of the Image Processing Software Based on the Infrared Image Feature Matching

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Book cover Cyber Security Intelligence and Analytics (CSIA 2019)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 928))

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Abstract

The infrared image has some disadvantages, such as the narrow dynamic range, the low contrast and the susceptibility to the noise pollution. The traditional infrared image denoising algorithm filters out the image details while removing the noise. A new method of the infrared image denoising based on the sparse representation is proposed. Firstly, the original infrared image is clustered, and then each clustered sub-image is decomposed into a dictionary, and the denoised infrared image is reconstructed from the sparse coefficient matrix.

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References

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Acknowledgment

Henan key task project in scientific and technological research, Project Number: 172102210414.

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Authors and Affiliations

  1. Nanyang Institute of Technology, Nanyang, 473000, Henan, China

    Fei Tian & Shilin Cui

Authors
  1. Fei Tian
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  2. Shilin Cui
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Corresponding author

Correspondence to Fei Tian .

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Editors and Affiliations

  1. Shanghai University, Shanghai, China

    Zheng Xu

  2. University of Texas at San Antonio, San Antonio, TX, USA

    Kim-Kwang Raymond Choo

  3. University of Guelph, Guelph, ON, Canada

    Ali Dehghantanha

  4. Kennesaw State University, Marietta, GA, USA

    Reza Parizi

  5. Manchester Metropolitan University, Stockport, UK

    Mohammad Hammoudeh

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Tian, F., Cui, S. (2020). Design and Implementation of the Image Processing Software Based on the Infrared Image Feature Matching. In: Xu, Z., Choo, KK., Dehghantanha, A., Parizi, R., Hammoudeh, M. (eds) Cyber Security Intelligence and Analytics. CSIA 2019. Advances in Intelligent Systems and Computing, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-030-15235-2_6

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