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A Meaningful Image Encryption Algorithm Based on Prediction Error and Wavelet Transform

by Mengling Zou, Zhengxuan Liu, Xianyi Chen

1 School of Computer and Software Nanjing University of Information Science & Technology, Nanjing, China.

* Corresponding Author: Xianyi Chen. Email: email.

Journal on Big Data 2019, 1(3), 151-158. https://doi.org/10.32604/jbd.2019.09057

Abstract

Image encryption (IE) is a very useful and popular technology to protect the privacy of users. Most algorithms usually encrypt the original image into an image similar to texture or noise, but texture and noise are an obvious visual indication that the image has been encrypted, which is more likely to cause the attacks of enemy. To overcome this shortcoming, many image encryption systems, which convert the original image into a carrier image with visual significance have been proposed. However, the generated cryptographic image still has texture features. In line with the idea of improving the visual quality of the final password images, we proposed a meaningful image hiding algorithm based on prediction error and discrete wavelet transform. Lots of experimental results and safety analysis show that the proposed algorithm can achieve high visual quality and ensure the security at the same time.

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Cite This Article

APA Style
Zou, M., Liu, Z., Chen, X. (2019). A meaningful image encryption algorithm based on prediction error and wavelet transform. Journal on Big Data, 1(3), 151-158. https://doi.org/10.32604/jbd.2019.09057
Vancouver Style
Zou M, Liu Z, Chen X. A meaningful image encryption algorithm based on prediction error and wavelet transform. J Big Data . 2019;1(3):151-158 https://doi.org/10.32604/jbd.2019.09057
IEEE Style
M. Zou, Z. Liu, and X. Chen, “A Meaningful Image Encryption Algorithm Based on Prediction Error and Wavelet Transform,” J. Big Data , vol. 1, no. 3, pp. 151-158, 2019. https://doi.org/10.32604/jbd.2019.09057



cc Copyright © 2019 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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