DocumentCode :
1929550
Title :
A Blind Watermarking Optimal Detection Based on the Wavelet Transform Domain
Author :
Liu, Xiao-yun ; Kun, Gao ; Chen, Wu-fan
Author_Institution :
Univ. of Electron. Sci. & Technol. of China, Chengdu
Volume :
3
fYear :
2007
fDate :
19-22 Aug. 2007
Firstpage :
1779
Lastpage :
1783
Abstract :
A performance of watermarking scheme relies heavily on the design of the detection. However, most of watermark detection algorithms in the literature are not optimum. Based on the generalized Gaussian distribution model of wavelet coefficients, an adaptive optimal blind watermarking detection is deduced and presented in this paper. Used an asymptotically optimal detection, it is an adaptive blind watermarking detection with the estimate of the shape parameter of wavelet coefficients. A series of experimental results which demonstrate the effectiveness of detector show that it is more validity and practicability than the correlation detector.
Keywords :
Gaussian distribution; image coding; watermarking; wavelet transforms; Gaussian distribution model; blind watermarking detection algorithm; wavelet transform domain; Cybernetics; Detectors; Gaussian distribution; Machine learning; Shape; Testing; Watermarking; Wavelet coefficients; Wavelet domain; Wavelet transforms; Asymptotically optimal detection; Blind watermarking; Generalized gaussian distribution; Shape parameter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Machine Learning and Cybernetics, 2007 International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-0973-0
Electronic_ISBN :
978-1-4244-0973-0
Type :
conf
DOI :
10.1109/ICMLC.2007.4370436
Filename :
4370436
Link To Document :
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