DocumentCode :
1765063
Title :
Designing an Efficient Image Encryption-Then-Compression System via Prediction Error Clustering and Random Permutation
Author :
Jiantao Zhou ; Xianming Liu ; Au, Oscar C. ; Yuan Yan Tang
Author_Institution :
Dept. of Comput. & Inf. Sci., Univ. of Macau, Taipa, China
Volume :
9
Issue :
1
fYear :
2014
fDate :
Jan. 2014
Firstpage :
39
Lastpage :
50
Abstract :
In many practical scenarios, image encryption has to be conducted prior to image compression. This has led to the problem of how to design a pair of image encryption and compression algorithms such that compressing the encrypted images can still be efficiently performed. In this paper, we design a highly efficient image encryption-then-compression (ETC) system, where both lossless and lossy compression are considered. The proposed image encryption scheme operated in the prediction error domain is shown to be able to provide a reasonably high level of security. We also demonstrate that an arithmetic coding-based approach can be exploited to efficiently compress the encrypted images. More notably, the proposed compression approach applied to encrypted images is only slightly worse, in terms of compression efficiency, than the state-of-the-art lossless/lossy image coders, which take original, unencrypted images as inputs. In contrast, most of the existing ETC solutions induce significant penalty on the compression efficiency.
Keywords :
arithmetic codes; data compression; image coding; pattern clustering; prediction theory; random codes; ETC; arithmetic coding-based approach; image encryption-then-compression system design; lossless compression; lossless image coder; lossy compression; lossy image coder; prediction error clustering; random permutation; security; Bit rate; Decoding; Encryption; Image coding; Image reconstruction; Compression of encrypted image; encrypted domain signal processing;
fLanguage :
English
Journal_Title :
Information Forensics and Security, IEEE Transactions on
Publisher :
ieee
ISSN :
1556-6013
Type :
jour
DOI :
10.1109/TIFS.2013.2291625
Filename :
6670767
Link To Document :
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