| Paper: | WA-P7.3 |
| Session: | Security V: Watermarking |
| Time: | Wednesday, September 19, 09:50 - 12:30 |
| Presentation: |
Poster
|
| Title: |
ADDITIVE WATERMARK DETECTORS BASED ON A NEW HIERARCHICAL SPATIALLY ADAPTIVE IMAGE MODEL |
| Authors: |
Antonis Mairgiotis; University of Ioannina | | |
| | Nikolaos Galatsanos; University of Ioannina | | |
| | Yongyi Yang; Illinois Institute of Technology | | |
| Abstract: |
In this paper we propose a new family of watermark detectors for additive watermarks in digital images. These detectors are based on a recently proposed two-level, hierarchical image model, which was found to be beneficial for image recovery problems. The top level of this model is defined to exploit the spatially-varying local statistics of the image, while the bottom level is used to characterize the image variations along two principal directions. Based on this model we derive a class of detectors for the additive watermark detection problem, including the generalized likelihood ratio test (GLRT) and Rao detectors. |
