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Hybrid Domain Encryption Method of Hyperspectral Remote Sensing Image

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Advances in Multimedia Information Processing – PCM 2017 (PCM 2017)

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Abstract

With the rapid development of remote sensing technology, hyperspectral remote sensing image as foundation data containing abundant sensitive information has been widely applied in many fields, such as agriculture, resources, ocean, city, and environment, etc. A hybrid domain encryption method is proposed for securely transmitting and storing hyperspectral remote sensing images. Considering the spatial and spectral characteristics, the hyperspectral image is encrypted in hybrid domain (spatial and spectral). Spatial domain encryption is done by using the composite chaos sequences. Then, the spectral sequence is scrambled by the cipher sequence for protecting the spectral feature of the hyperspectral image. Finally, the spectral and spatial information is mixed by a one-to-one mapping. Experimental results on NASA datasets show that our method can effectively protect both spectral and spatial feature of hyperspectral image compared with the other methods.

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Acknowledgments

The work in this paper is supported by the National Natural Science Foundation of China (No. 61370189, No. 61531006, No. 61372149, and No. 61471013), the Beijing Natural Science Foundation (No. 4163071), the Science and Technology Development Program of Beijing Education Committee (No. KM201510005004), the Importation and Development of High-Caliber Talents Project of Beijing Municipal Institutions (No. CIT&TCD20150311), Funding Project for Academic Human Resources Development in Institutions of Higher Learning Under the Jurisdiction of Beijing Municipality.

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Correspondence to Jing Zhang .

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Geng, W., Zhang, J., Chen, L., Li, J., Zhuo, L. (2018). Hybrid Domain Encryption Method of Hyperspectral Remote Sensing Image. In: Zeng, B., Huang, Q., El Saddik, A., Li, H., Jiang, S., Fan, X. (eds) Advances in Multimedia Information Processing – PCM 2017. PCM 2017. Lecture Notes in Computer Science(), vol 10736. Springer, Cham. https://doi.org/10.1007/978-3-319-77383-4_87

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  • DOI: https://doi.org/10.1007/978-3-319-77383-4_87

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-77382-7

  • Online ISBN: 978-3-319-77383-4

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