In digital watermarking, one aim is to insert the maximum possible watermark signal without significantly affecting image quality. Advantage can be taken of the masking effect of the eye to increase the signal strength in busy or high contrast image areas. The application of such a human visual system model to watermarking has been proposed by several authors. However if a simple contrast measurement is used, an objectionable ringing effect may become visible on connected directional edges. In this paper we describe a method which distinguishes between connected directional edges and high frequency textured areas, which have no preferred edge direction. The watermark gain on connected directional edges is suppressed, while the gain in high contrast textures is increased. Overall, such a procedure accommodates a more robust watermark for the same level of visual degradation because the watermark is attenuated where it is truly objectionable, and enhanced where it is not. Furthermore, some authors propose that the magnitude of a signal which can be imperceptibly placed in the presence of a reference signal can be described by a non-linear mapping of magnitude to local contrast. In this paper we derive a mapping function experimentally by determining the point of just noticeable difference between a reference image and a reference image with watermark.
[1]
Jae S. Lim,et al.
Two-Dimensional Signal and Image Processing
,
1989
.
[2]
J. Canny.
A Computational Approach to Edge Detection
,
1986,
IEEE Transactions on Pattern Analysis and Machine Intelligence.
[3]
Christophe De Vleeschouwer,et al.
Watermarking algorithm based on a human visual model
,
1998,
Signal Process..
[4]
Peter G. J. Barten,et al.
Contrast sensitivity of the human eye and its e ects on image quality
,
1999
.
[5]
John F. Canny,et al.
A Computational Approach to Edge Detection
,
1986,
IEEE Transactions on Pattern Analysis and Machine Intelligence.
[6]
Wenjun Zeng,et al.
Image-adaptive watermarking using visual models
,
1998,
IEEE J. Sel. Areas Commun..
[7]
Jorge Herbert de Lira,et al.
Two-Dimensional Signal and Image Processing
,
1989
.