The effect of matching watermark and compression transforms in compressed color images

The growth of networked multimedia systems has complicated copyright enforcement relative to digital images. One way to protect the copyright of digital images is to add an invisible structure to the image (known as a digital watermark) to identify the owner. In particular, it is important for Internet and image database applications that as much of the watermark as possible remain in the image after compression. Image adaptive watermarks are particularly resistant to removal by signal processing attack such as filtering or compression. Common image adaptive watermarks operate in the transform domain (DCT or wavelet); the same domains are also used for popular image compression techniques (JPEG, EZW). This paper investigates whether matching the watermarking domain to the compression transform domain will make the watermark more robust to compression.

[1]  Wenjun Zeng,et al.  Image-adaptive watermarking using visual models , 1998, IEEE J. Sel. Areas Commun..

[2]  Edward J. Delp,et al.  Color image compression using an embedded rate scalable approach , 1997, Proceedings of International Conference on Image Processing.

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

[4]  Edward J. Delp,et al.  Wavelet based rate scalable video compression , 1999, IEEE Trans. Circuits Syst. Video Technol..

[5]  M. Yeung,et al.  Can invisible watermarks resolve rightful ownerships? , 1997, Electronic Imaging.

[6]  Edward J. Delp,et al.  Overview of image security techniques with applications in multimedia systems , 1998, Other Conferences.

[7]  Edward J. Delp,et al.  A watermark for digital images , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.

[8]  William A. Pearlman High-performance low-complexity image compression , 1997, Optics & Photonics.

[9]  Jerome M. Shapiro,et al.  Embedded image coding using zerotrees of wavelet coefficients , 1993, IEEE Trans. Signal Process..

[10]  William A. Pearlman,et al.  A new, fast, and efficient image codec based on set partitioning in hierarchical trees , 1996, IEEE Trans. Circuits Syst. Video Technol..

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

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

[13]  Andrew B. Watson,et al.  The cortex transform: rapid computation of simulated neural images , 1987 .

[14]  Edward J. Delp,et al.  Perceptual watermarks for digital images and video , 1999, Electronic Imaging.

[15]  Wenjun Zeng,et al.  Digital image watermarking using visual models , 1997, Electronic Imaging.

[16]  Ahmed H. Tewfik,et al.  Multimedia data-embedding and watermarking technologies , 1998, Proc. IEEE.

[17]  John D. Villasenor,et al.  Visual thresholds for wavelet quantization error , 1996, Electronic Imaging.

[18]  Edward J. Delp,et al.  Evaluation of color-embedded wavelet image compression techniques , 1998, Electronic Imaging.

[19]  J. M. Foley,et al.  Contrast masking in human vision. , 1980, Journal of the Optical Society of America.