Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1180
Title: Watermark extraction by magnifying noise and applying global minimum decoder
Authors: Pan, Zhigeng
Li, Li
Zhang, Mingmin
Zhang, David D.
Subjects: Algorithms
Approximation theory
Error analysis
Fast Fourier transforms
Image analysis
Image quality
Information analysis
Mathematical models
Issue Date: 2004
Publisher: IEEE Computer Society
Source: Proceedings of the third International Conference on Image and Graphics : Hong Kong, China, 18-20 December 2004, p. 349-352.
Abstract: For the classical watermark embedment model I = I + αW , the corresponding watermark detection has its limitation in its need of a fixed parameter for extracting watermarks. If the extraction parameter is too large, we cannot extract the watermark from the image that contains watermarks; if it is too small, the extracted watermarks may be blurred. This paper proposes a novel watermark extraction method. First, we treat the watermark information as noise for the watermarked image in its spatial domain. We then magnify the noise before detection. Next, we recover the watermark information by adjusting the extracted data from the frequency domain according to our global minimum method. Experimental results show that our watermark extraction method is more valid and accurate than the classical method. It can greatly reduce extraction errors.
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Type: Conference Paper
URI: http://hdl.handle.net/10397/1180
ISBN: 0-7695-2244-0
Appears in Collections:COMP Conference Papers & Presentations

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