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Hyperspectral image coding and transmission scheme based on wavelet transform and distributed source coding

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Abstract

This paper presents a novel scheme for satellite hyperspectral images broadcasting over wireless channels. First, a simple pre-processing is performed. Then, a new hyperspectral band ordering algorithm that improves the compression performance is implemented. The ordered image data is also normalized. The discrete wavelet transform with three-level decomposition is used to divide each hyperspectral image band into ten wavelet sub-bands; nine of them are the details and the last LL-LL-LL is an approximation version of the band. Coset coding based on distributed source coding (DSC) is used for the LL-LL-LL sub-band to achieve high compression efficiency and low encoding complexity. Then, without syndrome coding, the transmission power is allocated directly to the band details and coset values according to their distributions and magnitudes without forward error correction (FEC). Finally, these data are transformed by the Hadamard matrix and transmitted over a dense constellation. Satellite hyperspectral images from an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) satellite are used for the validation of the proposed scheme. Experimental results demonstrate that the proposed scheme improves the average image quality by 6.91, 3.00 and 7.68 dB over LineCast, SoftCast-3D, and Softcast-2D, respectively. It also achieves up to a 5.63 dB gain over JPEG2000 with FEC.

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Acknowledgements

This work was supported in part by the National Science Foundation of China (NSFC) under grants 61472101, 61631017 and 61390513, the Major State Basic Research Development Program of China (973 Program 2015CB351804), and the National High Technology Research and Development Program of China (863 Program 2015AA015903). The authors would like to thank Prof. Dr. Michel Barret and Dr. Ibrahim Omara for their support in this work and also the anonymous reviewers for their valuable comments that greatly improved this paper.

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Authors and Affiliations

  1. Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, People’s Republic of China

    Ahmed Hagag & Xiaopeng Fan

  2. Department of Information Technology, Faculty of Information Technology, Egyptian E-Learning University, Dokki, Giza, 12611, Egypt

    Ahmed Hagag

  3. Department of Electronics and Electrical Communications, Faculty of Electronic Engineering, Menoufia University, Menouf, 32952, Egypt

    Fathi E. Abd El-Samie

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  1. Ahmed Hagag
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  2. Xiaopeng Fan
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  3. Fathi E. Abd El-Samie
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Correspondence to Ahmed Hagag.

Additional information

This work was supported in part by the National Science Foundation of China (NSFC) under grants 61472101, 61631017 and 61390513, the Major State Basic Research Development Program of China (973 Program 2015CB351804), and the National High Technology Research and Development Program of China (863 Program 2015AA015903).

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Hagag, A., Fan, X. & Abd El-Samie, F.E. Hyperspectral image coding and transmission scheme based on wavelet transform and distributed source coding. Multimed Tools Appl 76, 23757–23776 (2017). https://doi.org/10.1007/s11042-016-4158-8

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  • DOI: https://doi.org/10.1007/s11042-016-4158-8

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