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This paper presents a novel robust watermarking approach called FuseMark based on the principles of image fusion for copy protection or robust tagging applications. We consider the problem of logo watermarking in still images and employ multiresolution data fusion principles for watermark embedding and extraction. A human visual system model based on contrast sensitivity is incorporated to hide a higher energy hidden logo in salient image components. Watermark extraction involves both characterization of attacks and logo estimation using a rake-like receiver. Statistical analysis demonstrates how our extraction approach can be used for watermark detection applications to decrease the problem of false negative detection without increasing the false positive detection rate. Simulation results verify theoretical observations and demonstrate the practical performance of FuseMark.