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Title: Image compression and watermarking in the wavelet transform domain
Author: Khelifi, Fouad
ISNI:       0000 0001 3598 655X
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2007
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This thesis is concerned with an investigation into novel image compression and watermarking techniques in the wavelet transform domain. Compression refers to the reduction in the representative bit-budget of data with an acceptable distortion. Such an application is widely encountered in our daily life as a requirement due to the rapid growth of digital multimedia technology that overwhelms the ca- .pacity of the available communication channels. Watermarking is the process of embedding a hidden pattern, called watermark, that represents the ownership of an authorized user into a host data. Watermarking systems are expected to play an important role in meeting at least two major challenges: Imperceptibility of the watermark and the robustness to intentional and unintentional data manipulations. Driven by the urgent need to protect digital media content that is being broadly distributed and shared through the Internet by an ever-increasing number of users, the field of digital watermarking has witnessed an extremely fast-growing development over the last decade. The first part of the thesis addresses the compression of digital images with state-of-the-art wavelet-based coders. Image compression is basically achieved by reducing the statistical redundancy existing within the data. The wavelet transform efficiently reduces such a redundancy and exhibits different attractive features exploitable by the most powerful coders available in the literature. In this thesis, we propose efficient extensions of the much celebrated scalable SPIRT coder to color and multispectral image compression. Also an efficient SPECK-based lossless coder is proposed for multispectral data. The idea is to adjust the algorithms in order to join each group of two consecutive bands as they show high similarities and strong correlation. In the second pat of this thesis, watermarking in the transform domain is addressed. Different transforms are considered and a number of the most efficient multiplicative watermark detectors are assessed. We show the advantages/disadvantages of each transform domain for watermarking in a comparative study. Also, an essential enhancement is introduced to the optimum detection rule which is shown to be more accurate and efficient. An adaptive watermarking technique is also proposed in the wavelet transform domain that exploits the characteristics of the human visual system. It is. shown to outperform the conventional wavelet-based technique. Finally, watermarking in the compressed domain is discussed and a new robust watermarking scheme in the SPIRT-compressed bit-stream is presented.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available