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Title: Watermark extraction by magnifying noise and applying global minimum decoder
Authors: Pan, Z
Li, L
Zhang, M
Zhang, DD 
Issue Date: 2004
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.
Keywords: Algorithms
Approximation theory
Error analysis
Fast Fourier transforms
Image analysis
Image quality
Information analysis
Mathematical models
Publisher: IEEE Computer Society
ISBN: 0-7695-2244-0
Rights: © 2004 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
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