Volume 11 Number 5 (Sep. 2016)
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JCP 2016 Vol.11(5): 380-399 ISSN: 1796-203X
doi: 10.17706/jcp.11.5.380-399

A Critical Study on Encryption Based Compression Techniques

C. Sankara Narayanan, S. Anna Durai
1Research Scholar, Anna University, Principal of Government Polytechnic College, Chennai 600012, Tamil Nadu, India.
2Principal, Sri Krishna College of Engineering and Technology, Coimbatore, Tamil Nadu, India.


Abstract—The main goal of this study is to present an overview on the various encryption based compression techniques. By surveying the various encryption, compression and embedding techniques, the optimal encryption based compression technique is estimated. In communication systems, the data from the source is first compressed and then encrypted before forwarding over a channel to the receiver. But, in multiple practical scenarios, the image encryption has to be performed prior to the image compression. This leads to the problem of how to formulate the combination of encryption and compression algorithms. Compressing the image after encryption is found to be more efficient. For the image encryption, the input images are initially transformed. The encrypted images are then compressed and reconstructed using standard algorithms. This paper presents a survey on the various image encryption algorithms such as Blowfish algorithm, RC4, Data Encryption Standard (DES), etc. Further, the various image embedding techniques such as Discrete Wavelet Transform (DWT), Undecimated Wavelet Transform (UWT), etc., and the various compression techniques such as Set Partitioning in Hierarchical Trees (SPIHT), Arithmetic Encoding (AE), etc., are surveyed. The analysis results show that the combination of the Blowfish, RC4, UWT and SPIHT can provide high quality reconstructed image.

Index Terms—Encryption based image compression, compression algorithms, image embedding, and image security.

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Cite: C. Sankara Narayanan, S. Anna Durai, "A Critical Study on Encryption Based Compression Techniques," Journal of Computers vol. 11, no. 5, pp. 380-399, 2016.

General Information

ISSN: 1796-203X
Abbreviated Title: J.Comput.
Frequency: Bimonthly
Editor-in-Chief: Prof. Liansheng Tan
Executive Editor: Ms. Nina Lee
Abstracting/ Indexing: DBLP, EBSCO,  ProQuest, INSPEC, ULRICH's Periodicals Directory, WorldCat, CNKI,etc
E-mail: jcp@iap.org
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