Fractal-Based Secured Multiple-Image Compression and Distribution

Fractal-Based Secured Multiple-Image Compression and Distribution

Hsuan T. Chang (National Yunlin University of Science and Technology, Taiwan) and Chih-Chung Hsu (National Yunlin University of Science and Technology and National Tsing Hua University, Taiwan)
Copyright: © 2009 |Pages: 18
DOI: 10.4018/978-1-60566-262-6.ch027
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This chapter introduces a pioneer concept in which multiple images are simultaneously considered in the compression and secured distribution frameworks. We have proposed the so-called fractal mating coding scheme to successfully implement the joint image compression and encryption concept through a novel design in the domain pool construction. With the exploration of the intra- and inter-image similarity among multiple images, not only the coding performance can be improved, but also the secured image distribution purpose can be achieved. The authors hope that the revealed fractal-based ideas in this chapter will provide a different perspective for the image compression and distribution framework.
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Recently, the algorithms for multimedia content compression, protection, and transmission through the Internet have been drastically developed. For secured data transformation, cryptography such as Data Encryption Standard (DES) or Advanced Encryption Standard (AES) is very commonly used to prevent from illegal steals. For multimedia contents such as images and videos, watermarking (Cox, 1997; Hsu, 1999; Lin, 2005; Podilchuk, 2001), secure image coding/encryption (Dang, 2000; Yeo, 2000), and/or image secret sharing schemes (Naor, 1995) are used. By using watermarking schemes one can claim the data authority via the insertion of visible or invisible marks. Image encryption schemes (Imaizumi, 2005; Lian, 2004; Lukac, 2005a; Martin, 2005; Sinha, 2005) shuffle the original content into noise-like data, which cannot be correctly reconstructed without the secret keys used in the encryption stage. On the other hand, modern image secret sharing schemes (Guo, 2003; Lin, 2005; Lukac, 2004; Lukac, 2005b; Lukac, 2005c; Lukac, 2005d; Sudharsan, 2005) are based on visual cryptography (Hou, 2003; Jin, 2005) and human visual system characteristics (Tsai, 2004). Since a secret image can be recovered without any computation, the disadvantage of complex computation required in traditional cryptography can be released.

Key Terms in this Chapter

Mating Ratio: The percentage of the domain blocks selected from a specific image.

Joint Compression and Encryption: Image encryption is simultaneously performed in the compression stage.

Domain Pool: Constructed by the domain blocks, which are used for searching the similarity in images.

Mating Table: A binary array which is used to shuffle the fractal codes of two or more images.

Fractal Image Coding: Search for the self similarity in an image and then the parameters denoting the contractive affine transformation between the domain and range blocks are recorded to perform image compression.

Mating Coding: Consider the compression of two or more images. While compressing one of images, the information in other images is also utilized. In decoding, therefore, the information from other images is required.

Inter-Image Similarity: (1) Self-similarity; the similarity exists within an image; (2) The similarity of the contents among different images.

Image Encryption: To protect the image content from illegal users, some schemes are used to make the original plain image become unrecognizable.

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