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International Conference on Machine Learning for Cyber Security

ML4CS 2020: Machine Learning for Cyber Security pp 215–226Cite as

Image Dust Storm Synthetic Method Based on Optical Model

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12488))

Abstract

To address the problem that the dusty image dataset is small and difficult to collect, this paper presents a synthetic method for generating dusty image based on a classical optical model. The proposed method first learns the physical process of generating dusty image according to the classical optical model. Then, the transmission map is estimated and combined with the presupposed dust storm color map as inputs for obtaining a synthetic dusty image. Finally, considering the impact of image scene depth on the synthesis of dusty image, the proposed method selects an appropriate value of input parameter to obtain final synthetic dusty image. Experimental results on an image dataset captured in clear weather show that the synthetic dusty images obtained by the proposed method can be used as a good substitute for real dusty images.

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Acknowledgment

This work is partially supported by National Natural Science Foundation of China (61972187, 61772254), Fujian Provincial Leading Project (2017H0030, 2019H0025), Government Guiding Regional Science and Technology Development (2019L3009), and Natural Science Foundation of Fujian Province (2017J01-768 and 2019J01756).

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Authors and Affiliations

  1. College of Mathematics and Computer Science, Fuzhou University, Fuzhou, 350108, China

    Jiayan Huang

  2. Fujian Provincial Key Laboratory of Information Processing and Intelligent Control, College of Computer and Control Engineering, Minjiang University, Fuzhou, 350121, China

    Zuoyong Li

  3. School of Computer Science and Technology, Harbin University of Science and Technology, Harbin, 150080, China

    Chuansheng Wang

Authors
  1. Jiayan Huang
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  2. Zuoyong Li
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  3. Chuansheng Wang
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Corresponding author

Correspondence to Zuoyong Li .

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Editors and Affiliations

  1. Xidian University, Xi'an, China

    Xiaofeng Chen

  2. Guangzhou University, Guangzhou, China

    Hongyang Yan

  3. Michigan State University, East Lansing, MI, USA

    Qiben Yan

  4. Division of Computer, Electrical and Mathematical Sciences and Engineering, King Abdullah University of Science, Thuwal, Saudi Arabia

    Xiangliang Zhang

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Huang, J., Li, Z., Wang, C. (2020). Image Dust Storm Synthetic Method Based on Optical Model. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12488. Springer, Cham. https://doi.org/10.1007/978-3-030-62463-7_20

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  • DOI: https://doi.org/10.1007/978-3-030-62463-7_20

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62462-0

  • Online ISBN: 978-3-030-62463-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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