By Frank Y. Shih
ISBN-10: 1315121107
ISBN-13: 9781315121109
ISBN-10: 1498738761
ISBN-13: 9781498738767
This ebook intends to supply a accomplished review on diversified facets of mechanisms and strategies for info safeguard. it really is written for college kids, researchers, and execs learning within the box of multimedia protection and steganography. Multimedia safety and steganography is mainly appropriate as a result of the worldwide scale of electronic multimedia and the fast development of the web. electronic watermarking expertise can be utilized to assure authenticity and will be utilized as evidence that the content material has no longer been altered on account that insertion. up to date innovations and advances in watermarking are explored during this new version. The combinational spatial and frequency domain names watermarking method offers a brand new notion of enlarging the embedding ability of watermarks. The genetic set of rules (GA) dependent watermarking strategy solves the rounding blunders challenge and supply a good embedding procedure. every one bankruptcy presents the reader with a primary, theoretical framework, whereas constructing the large complicated strategies and contemplating the basic rules of the electronic watermarking and steganographic structures. numerous powerful algorithms which are provided all through illustrate the framework and supply information and instruments in realizing and enforcing the basic principles.
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Extra info for Digital Watermarking and Steganography: Fundamentals and Techniques
Sample text
However, the sampling could be more efficient using the Nyquist rule. 11) s2 where N 1 and N 2 denote the number of samples at scales s 1 and s 2 , respectively, and s 2 > s 1 . This rule means that at higher scales (lower frequencies), the number of samples can be decreased. The sampling rate obtained is the minimum rate that allows the original signal to be reconstructed from a discrete set of samples. A dyadic scale satisfies the Nyquist rule by discretizing the scale parameter into a logarithmic series, and the time parameter is then discretized with respect to the corresponding scale parameters.
We can embed the watermark into the coefficients of a transformed image in the frequency domain [3,14]. The transformations include discrete cosine transform, discrete Fourier transform, and discrete wavelet transform. However, if we embed too much data in the frequency domain, the image quality will be degraded significantly. Spatial domain watermarking techniques are usually less robust to attacks such as compression and added noise. However, they have much lower computational complexity and usually can survive a cropping attack, which frequency domain watermarking techniques often fail to do.
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