Multiplicative watermarking algorithm based on wavelet visual model
Er-song HUANG1,Jin-hua LIU2,Ru-hong WEN3
1. Department of Information Technology, Yingtan College of Jiangxi Normal University, Yingtan Jiangxi 335000, China
2. School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu Sichuan 611731, China
3. Physical Science and Technology College, Yichun University, Yichun Jiangxi 336000, China
Abstract：The additive watermarking algorithm has good imperceptibility, however, the robustness of watermark is poor. As a result, a multiplicative image watermarking method was proposed by combining the visual model in the wavelet domain. In the proposed embedding scheme, the middle-frequency subband acted as the watermark embedding space, which was used to achieve the tradeoff between the imperceptibility and the robustness of watermarking system. Besides, the embedding strength factor was determined by considering the frequency masking, luminance masking and texture masking of host image. In the proposed detection scheme, the probability density function of wavelet coefficients was modeled by the Generalized Gaussian Distribution (GGD), and the watermark decision threshold was obtained by using the Neyman-Pearson (NP) criterion, and the Receiver Operating Characteristic (ROC) curve between the probability of false alarm and the probability of detection was derived. Finally, the robustness of the proposed watermarking was tested when being against common image processing attacks such as JPEG compression, Additive White Gaussian Noise (AWGN), scaling and cropping. The experimental results demonstrate that the proposed method has good detection performance and good robustness.
LANGELAAR G C, SETYAWAN I, LAGENDIJK R L. Watermarking digital image and video data: A state-of-the-art overview [J]. IEEE Transactions on Signal Processing, 2000, 17(5): 20-46.
[2]
BI NING, SUN QIYU, HUANG DAREN, et al. Robust image watermarking based on multiband wavelets and empirical mode decomposition [J]. IEEE Transactions on Image Processing, 2007, 16(8): 1956-1967.
[3]
ZHENG DONG, WANG SHA, ZHAO JIYING. RST invariant image watermarking algorithm with mathematical modeling and analysis of the watermarking processes [J]. IEEE Transactions on Image Processing, 2009, 18(5): 1055-1067.
COX I, KILIAN J, LEIGHTON T, et al. Secure spread spectrum watermarking for multimedia [J]. IEEE Transactions on Image Processing, 1997, 12(6): 1673-1678.
[6]
BRIASSOULI A, TSAKALIDES P, STOURAITIS A. Hidden messages in heavy-tails: DCT-domain watermark detection using Alpha-stable models [J]. IEEE Transactions on Multimedia, 2005, 7(4): 700-715.
[7]
HERNANDEZ J R, AMADO M, PEREZ-GONZALEZ F. DCT-domain watermarking techniques for still images: Detector performance analysis and a new structure [J]. IEEE Transactions on Image Processing, 2000, 9(1): 55-68.
[8]
CHENG QIANG, HUANG T S. Robust optimum detection of transform domain multiplicative watermarks [J]. IEEE Transactions on Signal Processing, 2003, 51(4): 906-924.
[9]
LEWIS S, KNOWLES G. Image compressions using the 2-D wavelet transform [J]. IEEE Transactions on Image Processing, 1992, 2(1): 244 -250.
[10]
BARNI M, BARTOLINI F, PIVA A. Improved wavelet-based watermarking through pixel-wise masking [J]. IEEE Transactions on Image Processing, 2001, 10(5): 783-791.
[11]
BARNI M, BARTOLINI F, ROSA A, et al. Capacity of full frame DCT image watermarks [J]. IEEE Transactions on Image Processing, 2000, 9(8): 1450-1455.
[12]
WANG JINWEI, LIU GUANGJIE, DAI YUEWEI, et al. Locally optimum detection for Barni's multiplicative watermarking in DWT domain [J]. Signal Processing, 2008, 88(1): 117-130.
[13]
WANG ZHOU, BOVIK A C, SHEIKH H R, et al. Image quality assessment: From error visibility to structural similarity [J]. IEEE Transactions on Image Processing, 2004, 13(4): 600-612.
[14]
BRIASSOULI A, G.STRINTZIS M. Locally optimum nonlinearities for DCT watermark detection [J]. IEEE Transactions on Image Processing, 2004, 13(12): 1604-1607.
[15]
KWON S, LEE S, KWON K, et al. Watermark detection algorithm using statistical decision theory [C]// ICME'02: Proceedings of 2002 IEEE International Conference on Multimedia and Expo. Piscataway, NJ: IEEE Press, 2002: 561-564.
2011, Vol. 31 
