Watermarking capacity of digital images based on domain-specific masking effects

Our objective is to find a theoretical watermarking capacity bound of digital images based on domain-specific masking effects. We first show the capacity of private watermarking in which the power constraints are not uniform. Then, we apply several domain-specific Human Vision System approximation models to estimate the power constraints and then show the theoretical watermarking capacity of an image in a general noisy environment. Note that we consider all pixels, watermarks and noises to be discrete values, which occur in realistic cases.

[1]  Mauro Barni,et al.  Capacity of the watermark channel: how many bits can be hidden within a digital image? , 1999, Electronic Imaging.

[2]  Chun-Hsien Chou,et al.  A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile , 1994, Proceedings of 1994 IEEE International Symposium on Information Theory.

[3]  H. Wilson,et al.  Orientation bandwidths of spatial mechanisms measured by masking. , 1984, Journal of the Optical Society of America. A, Optics and image science.

[4]  Deepa Kundur Water-filling for watermarking? , 2000, 2000 IEEE International Conference on Multimedia and Expo. ICME2000. Proceedings. Latest Advances in the Fast Changing World of Multimedia (Cat. No.00TH8532).

[5]  Kannan Ramchandran,et al.  Capacity issues in digital image watermarking , 1998, Proceedings 1998 International Conference on Image Processing. ICIP98 (Cat. No.98CB36269).

[6]  Imre Csiszár,et al.  Capacity of the Gaussian arbitrarily varying channel , 1991, IEEE Trans. Inf. Theory.

[7]  Joan L. Mitchell,et al.  JPEG: Still Image Data Compression Standard , 1992 .

[8]  Ching-Yung Lin Watermarking and Digital Signature Techniques for Multimedia Authentication and Copyright Protection , 2000 .

[9]  John D. Villasenor,et al.  Visibility of wavelet quantization noise , 1997, IEEE Transactions on Image Processing.

[10]  Max H. M. Costa,et al.  Writing on dirty paper , 1983, IEEE Trans. Inf. Theory.

[11]  Shih-Fu Chang,et al.  Zero-error information hiding capacity of digital images , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[12]  Chun-Hsien Chou,et al.  A perceptually tuned subband image coder based on the measure of just-noticeable-distortion profile , 1995, IEEE Trans. Circuits Syst. Video Technol..

[13]  Andrew B. Watson,et al.  DCT quantization matrices visually optimized for individual images , 1993, Electronic Imaging.

[14]  Jeffrey Lubin,et al.  The use of psychophysical data and models in the analysis of display system performance , 1993 .

[15]  Scott J. Daly,et al.  Visible differences predictor: an algorithm for the assessment of image fidelity , 1992, Electronic Imaging.