A study of the obtainable watermark data rate for information hiding algorithms is presented in this paper. As the perceptual entropy for wideband monophonic audio signals is in the range of four to five bits per sample, a significant amount of additional information can be inserted into signal without causing any perceptual distortion. Experimental results showed that transform domain watermark embedding outperforms considerably watermark embedding in time domain and that signal decompositions with a high gain of transform coding, like the wavelet transform, are the most suitable for high data rate information hiding. Keywords?Digital watermarking, information hiding, audio watermarking, watermark data rate.
<p>[1] I. Cox, M. Miller, J. Bloom "Digital Watermarking," Morgan Kaufmann Publishers, San Francisco, CA, 2003.
[2] J. Chou, K. Ramchandran, A. Ortega "High capacity audio data hiding for noisy channels," in Proc. International Conference on Information Technology: Coding and Computing, Las Vegas, NV, 2001, pp. 108?111.
[3] S. Servetto, C. Podilchuk, K. Ramchandran "Capacity issues in digital image watermarking," in Proc. IEEE International Conference on Image Processing, Chicago, IL, 1998, pp 445?449.
[4] S. Pradhan, J. Chou, K. Ramchandran "Duality between source coding and channel coding and its extension to the side information case," IEEE Transactions on Information Theory, Vol. 49, No. 5, 2003, pp. 1181?1203.
[5] J. Johnston "Estimation of perceptual entropy using noise masking criteria," in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, New York, NY, 1998, pp. 2524?2527.
[6] J. Johnston "Transform coding of audio signals using perceptual noise criteria," IEEE Journal on Selected Areas in Communications, Vol. 6, No. 2, 1988, pp. 314?323.
[7] T. Cedric, R. Adi, I. McLaughlin "Data concealment in audio using a nonlinear frequency distribution of PRBS coded data and frequency-domain LSB insertion," in Proc. IEEE Region 10 International Conference on Electrical and Electronic Technology, Kuala Lumpur, Malaysia, 2000, pp. 275?278.
[8] M. Ramkumar, A. Akansu "Information theoretic bounds for data hiding in compressed images," in Proc. IEEE Workshop on Multimedia Signal Processing, Los Angeles, CA, 1998, pp 267?272.
[9] M. Ramkumar, A. Akansu "Capacity estimates for data hiding in compressed images," IEEE Journal on Selected Areas in Communications, Vol. 10, No. 8, 2001, pp. 1252?1263.
[10] Y. Lee, L. Chen "High capacity image steganographic model," IEE Proceedings on Vision, Image and Signal Processing, Vol. 147, No. 3, 2000, pp. 288?294.
[11] F. Hartung, B. Girod "Watermarking of uncompressed and compressed video," Signal Processing, Vol. 66, No. 3, 1998, pp. 283?301.
[12] B. Mobasseri "Direct sequence watermarking of digital video using m-frames,? in Proc. IEEE International Conference on Image Processing, Chicago, IL, 1998, pp. 399?403.
[13] J. Fridrich, M. Goljan, R. Du "Lossless data embedding - new paradigm in digital watermarking," Applied Signal Processing, Vol. 2002, No. 2, 2002, pp 185?196.
[14] Mallat S "Wavelet Tour of Signal Processing," Academic Press, San Diego, CA, 2001. World Academy of Science, Engineering and Technology 2 2007529</p>
<p>[1] I. Cox, M. Miller, J. Bloom "Digital Watermarking," Morgan Kaufmann Publishers, San Francisco, CA, 2003.
[2] J. Chou, K. Ramchandran, A. Ortega "High capacity audio data hiding for noisy channels," in Proc. International Conference on Information Technology: Coding and Computing, Las Vegas, NV, 2001, pp. 108?111.
[3] S. Servetto, C. Podilchuk, K. Ramchandran "Capacity issues in digital image watermarking," in Proc. IEEE International Conference on Image Processing, Chicago, IL, 1998, pp 445?449.
[4] S. Pradhan, J. Chou, K. Ramchandran "Duality between source coding and channel coding and its extension to the side information case," IEEE Transactions on Information Theory, Vol. 49, No. 5, 2003, pp. 1181?1203.
[5] J. Johnston "Estimation of perceptual entropy using noise masking criteria," in Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing, New York, NY, 1998, pp. 2524?2527.
[6] J. Johnston "Transform coding of audio signals using perceptual noise criteria," IEEE Journal on Selected Areas in Communications, Vol. 6, No. 2, 1988, pp. 314?323.
[7] T. Cedric, R. Adi, I. McLaughlin "Data concealment in audio using a nonlinear frequency distribution of PRBS coded data and frequency-domain LSB insertion," in Proc. IEEE Region 10 International Conference on Electrical and Electronic Technology, Kuala Lumpur, Malaysia, 2000, pp. 275?278.
[8] M. Ramkumar, A. Akansu "Information theoretic bounds for data hiding in compressed images," in Proc. IEEE Workshop on Multimedia Signal Processing, Los Angeles, CA, 1998, pp 267?272.
[9] M. Ramkumar, A. Akansu "Capacity estimates for data hiding in compressed images," IEEE Journal on Selected Areas in Communications, Vol. 10, No. 8, 2001, pp. 1252?1263.
[10] Y. Lee, L. Chen "High capacity image steganographic model," IEE Proceedings on Vision, Image and Signal Processing, Vol. 147, No. 3, 2000, pp. 288?294.
[11] F. Hartung, B. Girod "Watermarking of uncompressed and compressed video," Signal Processing, Vol. 66, No. 3, 1998, pp. 283?301.
[12] B. Mobasseri "Direct sequence watermarking of digital video using m-frames,? in Proc. IEEE International Conference on Image Processing, Chicago, IL, 1998, pp. 399?403.
[13] J. Fridrich, M. Goljan, R. Du "Lossless data embedding - new paradigm in digital watermarking," Applied Signal Processing, Vol. 2002, No. 2, 2002, pp 185?196.
[14] Mallat S "Wavelet Tour of Signal Processing," Academic Press, San Diego, CA, 2001. World Academy of Science, Engineering and Technology 2 2007529</p>
@article{"International Journal of Electrical, Electronic and Communication Sciences:60723", author = "Nedeljko Cvejic and Tapio Sepp", title = "Watermark Bit Rate in Diverse Signal Domains", abstract = "A study of the obtainable watermark data rate for information hiding algorithms is presented in this paper. As the perceptual entropy for wideband monophonic audio signals is in the range of four to five bits per sample, a significant amount of additional information can be inserted into signal without causing any perceptual distortion. Experimental results showed that transform domain watermark embedding outperforms considerably watermark embedding in time domain and that signal decompositions with a high gain of transform coding, like the wavelet transform, are the most suitable for high data rate information hiding. Keywords?Digital watermarking, information hiding, audio watermarking, watermark data rate.
", keywords = "Digital watermarking, information hiding, audio watermarking, watermark data rate.", volume = "1", number = "2", pages = "336-4", }
