Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1180
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dc.contributorDepartment of Computing-
dc.creatorPan, Z-
dc.creatorLi, L-
dc.creatorZhang, M-
dc.creatorZhang, DD-
dc.date.accessioned2014-12-11T08:27:12Z-
dc.date.available2014-12-11T08:27:12Z-
dc.identifier.isbn0-7695-2244-0-
dc.identifier.urihttp://hdl.handle.net/10397/1180-
dc.language.isoenen_US
dc.publisherIEEE Computer Societyen_US
dc.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.en_US
dc.rightsThis material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.en_US
dc.subjectAlgorithmsen_US
dc.subjectApproximation theoryen_US
dc.subjectError analysisen_US
dc.subjectFast Fourier transformsen_US
dc.subjectImage analysisen_US
dc.subjectImage qualityen_US
dc.subjectInformation analysisen_US
dc.subjectMathematical modelsen_US
dc.titleWatermark extraction by magnifying noise and applying global minimum decoderen_US
dc.typeConference Paperen_US
dc.description.otherinformationAuthor name used in this publication: David Zhangen_US
dc.description.otherinformationCenter for Multimedia Signal Processing and Department of Computingen_US
dcterms.abstractFor 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.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationProceedings of the third International Conference on Image and Graphics : Hong Kong, China, 18-20 December 2004, p. 349-352-
dcterms.issued2004-
dc.identifier.scopus2-s2.0-17044396643-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_IR/PIRAen_US
dc.description.pubStatusPublisheden_US
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