A new statistical detector for CT-based multiplicative image watermarking using the t location-scale distribution

In this study, a new statistical multiplicative watermark detector in contourlet domain is presented. The contourlet coefficients of images are highly non-Gaussian and a proper distribution to model the statistics of the contourlet coefficients is a heavy-tail Probability Distribution Function (PDF). In this study, a multiplicative watermarking scheme is proposed in the contourlet domain using t location-scale distribution (tLS). Afterward, we used the likelihood ratio decision rule and tLS distribution to design an optimal multiplicative watermark detector. The detector showed higher efficiency than other watermarking schemes in the literature, based on the experimental results, and its robustness against different attacks was verified.

[1]  Chaur-Heh Hsieh,et al.  A novel image watermarking scheme based on amplitude attack , 2007, Pattern Recognit..

[2]  M. Omair Ahmad,et al.  A Study of Multiplicative Watermark Detection in the Contourlet Domain Using Alpha-Stable Distributions , 2014, IEEE Transactions on Image Processing.

[3]  M. Omair Ahmad,et al.  Optimum multiplicative watermark detector in contourlet domain using the normal inverse Gaussian distribution , 2015, 2015 IEEE International Symposium on Circuits and Systems (ISCAS).

[4]  Seyed Mohammad Ahadi,et al.  A Robust Image Watermarking in the Ridgelet Domain Using Universally Optimum Decoder , 2010, IEEE Transactions on Circuits and Systems for Video Technology.

[5]  Thomas S. Huang,et al.  Robust optimum detection of transform domain multiplicative watermarks , 2003, IEEE Trans. Signal Process..

[6]  Ingemar J. Cox,et al.  Secure spread spectrum watermarking for multimedia , 1997, IEEE Trans. Image Process..

[7]  Song Guo,et al.  Robust Histogram Shape-Based Method for Image Watermarking , 2015, IEEE Transactions on Circuits and Systems for Video Technology.

[8]  Ioannis Pitas,et al.  An Optimal Detector Structure for the Fourier Descriptors Domain Watermarking of 2D Vector Graphics , 2007, IEEE Transactions on Visualization and Computer Graphics.

[9]  M. Do,et al.  Directional multiscale modeling of images using the contourlet transform , 2003, IEEE Workshop on Statistical Signal Processing, 2003.

[10]  Farrokh Marvasti,et al.  Contourlet-Based Image Watermarking Using Optimum Detector in a Noisy Environment , 2010, IEEE Transactions on Image Processing.

[11]  Minh N. Do,et al.  Ieee Transactions on Image Processing the Contourlet Transform: an Efficient Directional Multiresolution Image Representation , 2022 .

[12]  Mahmoud Ahmadian-Attari,et al.  A new detector for contourlet domain multiplicative image watermarking using Bessel K form distribution , 2016, J. Vis. Commun. Image Represent..

[13]  Maryam Amirmazlaghani,et al.  A novel robust scaling image watermarking scheme based on Gaussian Mixture Model , 2015, Expert Syst. Appl..

[14]  Maryam Amirmazlaghani,et al.  Additive watermark detector in contourlet domain using the t location-scale distribution , 2016, 2016 2nd International Conference of Signal Processing and Intelligent Systems (ICSPIS).

[15]  Ling-Yuan Hsu,et al.  Blind image watermarking via exploitation of inter-block prediction and visibility threshold in DCT domain , 2015, J. Vis. Commun. Image Represent..

[16]  Rabab Kreidieh Ward,et al.  Robust Image Watermarking Based on Multiscale Gradient Direction Quantization , 2011, IEEE Transactions on Information Forensics and Security.

[17]  Hamidreza Sadreazami,et al.  A robust spread spectrum based image watermarking in ridgelet domain , 2012 .

[18]  Maryam Amirmazlaghani,et al.  Additive watermark detection in the wavelet domain using 2D-GARCH model , 2016, Inf. Sci..