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|Title: ||Study of digital image watermarking in curvelet domain|
|Other Titles: ||Ji yu qu bo yu de shu ma tu xiang shui yin|
|Authors: ||Leung, Hon Yin (梁瀚賢)|
|Department: ||Department of Electronic Engineering|
|Degree: ||Master of Philosophy|
|Issue Date: ||2009|
|Publisher: ||City University of Hong Kong|
|Subjects: ||Digital watermarking.|
Watermarks -- Data processing.
|Notes: ||CityU Call Number: QA76.9.A25 L483 2009|
vii, 101 leaves : ill. 30 cm.
Thesis (M.Phil.)--City University of Hong Kong, 2009.
Includes bibliographical references (leaves 95-99)
|Abstract: ||The rapid development of Internet introduces a set of challenging problems
regarding security. Anyone can duplicate the digital data without other permissions.
Therefore, it raises the awareness of the copyright problems in the e-commerce age.
Digital watermarking is a technique of embedding a hidden signal into digital
contents to identify the legitimate owner, track unauthorized use or detect intentional
tampering of the original data. Many research papers are proposed to embed the
watermark in different frequency domains rather than in spatial domain for
increasing the robustness of watermark. For the same reason, this thesis focuses on
embedding the watermark into the Curvelet Transform developed by Candμes and
Donoho. It is proved that one can recover the object from noisy environment by
simple Curvelet wedges better than other transform. Therefore, Curvelet Transform
shows great potential for watermarking. Traditionally, Curvelet watermarks are
embedded into all frequency bands. However, the study of individual band or mixed
bands behavior and the use of them for watermarking have not been reported. As a
result, this thesis provides a detailed study of the watermarking using individual band
or mixed-bands based on the Curvelet Transform. The experimental results
demonstrate that the proposed algorithm can provide excellent robustness against
most image processing operations including jpeg compression, histogram
equalization, median filtering, Laplacian sharpening and Gaussian low-pass filtering.
In order to provide better perceptibility of the watermarked image, we have added a
Human Visual System model to improve the proposed algorithm. Comparisons of
other watermarking methods based on the Curvelet Transform have also been studied.|
|Online Catalog Link: ||http://lib.cityu.edu.hk/record=b2374881|
|Appears in Collections:||EE - Master of Philosophy |
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