Skip to main content
Article
Optimal image watermark decoding
Faculty of Informatics - Papers (Archive)
  • Wenming Lu, Unviersity of Wollongong
  • Wanqing Li, University of Wollongong
  • Reihaneh Safavi-Naini, University of Wollongong
  • Philip Ogunbona, University of Wollongong
RIS ID
17822
Publication Date
1-1-2006
Publication Details

Lu, W., Li, W., Safavi-Naini, R. & Ogunbona, P. O. (2006). Optimal image watermark decoding. In Y. Zhuang, S. Yang, Y. Rui & Q. He (Eds.), Pacific-Rim Conference on Multimedia (pp. 141-149). Germany: Springer-Verlag Berlin Heidelberg.

Abstract

Not much has been done in utilizing the available information at the decoder to optimize the decoding performance of watermarking systems. This paper focuses on analyzing different decoding methods, namely, Minimum Distance, Maximum Likelihood and Maximum a-posteriori decoding given varying information at the decoder in the blind detection context. Specifically, we propose to employ Markov random fields to model the prior information given the embedded message is a structured logo. The application of these decoding methods in Quantization Index Modulation systems shows that the decoding performance can be improved by Maximum Likelihood decoding that exploits the property of the attack and Maximum a-posteriori decoding that utilizes the modeled prior information in addition to the property of the attack.

Citation Information
Wenming Lu, Wanqing Li, Reihaneh Safavi-Naini and Philip Ogunbona. "Optimal image watermark decoding" (2006) p. 141 - 149
Available at: http://works.bepress.com/p_ogunbona/23/