New Additive Watermark Detectors Based On A Hierarchical Spatially Adaptive Image Model
| Autor: | Nikolas P. Galatsanos, Antonis Mairgiotis, Yongyi Yang |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Physics::Instrumentation and Detectors
Computer Networks and Communications Computer science business.industry Detector ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION Watermark Pattern recognition Image (mathematics) Digital image High Energy Physics::Experiment Artificial intelligence Safety Risk Reliability and Quality business Digital watermarking |
| Zdroj: | IEEE Transactions on Information Forensics and Security. 3:29-37 |
| ISSN: | 1556-6013 |
| DOI: | 10.1109/tifs.2007.916290 |
| Popis: | 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 hierarchical, two-level 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, which include a generalized likelihood ratio, Bayesian, and Rao test detectors. We also propose methods to estimate the necessary parameters for these detectors. Our numerical experiments demonstrate that these new detectors can lead to superior performance to several state-of-the-art detectors. |
| Databáze: | OpenAIRE |
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