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Compression of encrypted images with multi-layer decomposition

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Abstract

This work proposes a novel scheme of lossy compression for encrypted gray images. In the encryption phase, the original image is decomposed into a sub-image and several layers of prediction errors, and the sub-image and prediction errors are encrypted using an exclusive-or operation and a pseudo-random permutation, respectively. Although a channel provider does not know the cryptographic key and the original content, he can still effectively reduce the amount of encrypted data by quantizing the permuted prediction errors on various layers, and an optimization method with rate-distortion criteria can be employed to select the values of quantization steps. At receiver side with the knowledge of cryptographic key, a decoder integrating dequantization, decryption and image reconstruction functions is used to retrieve the principal content of original image from the compressed data. Experimental result shows the rate-distortion performance of the proposed scheme is significantly better than that of previous technique.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China under Grant 61073190, by the Research Fund for the Doctoral Program of Higher Education of China under Grant 20113108110010, and by the Program for Professor of Special Appointment (Eastern Scholar) at Shanghai Institutions of Higher Learning.

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Authors and Affiliations

  1. School of Communication and Information Engineering, Shanghai University, 149 Yanchang Road, Shanghai, 200072, People’s Republic of China

    Xinpeng Zhang, Guangling Sun & Liquan Shen

  2. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai, 200093, People’s Republic of China

    Chuan Qin

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  1. Xinpeng Zhang
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  2. Guangling Sun
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  3. Liquan Shen
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  4. Chuan Qin
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Correspondence to Xinpeng Zhang.

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Zhang, X., Sun, G., Shen, L. et al. Compression of encrypted images with multi-layer decomposition. Multimed Tools Appl 72, 489–502 (2014). https://doi.org/10.1007/s11042-013-1392-1

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  • DOI: https://doi.org/10.1007/s11042-013-1392-1

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