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A new curvelet-based watermarking technique is presented in this paper, in which watermark signals are selected to be a gray-scale logo image. The curvelet transform was developed in order to represent edges along curves much more efficiently than the traditional transforms. We apply the transform to watermarking and evaluate the effectiveness of the method. Our watermarking algorithm embeds a watermark in curvelet coefficients which are selected by a criterion whether they contain as much edge information as possible. We evaluated the effectiveness of the method against some watermark attacks. Experiment results show that our new method yields quite good visual quality in watermarked images, and is robust to typical signal processing attacks such as compression, cropping, adding noise and filtering.

We propose a robust digital watermarking technique based on Principal Component Analysis (PCA) and evaluate the effectiveness of the method against some watermark attacks. In this proposed method, watermarks are embedded in the PCA domain and the method is closely related to DCT or DWT based frequency-domain watermarking. The orthogonal basis functions, however, are determined by data and they are adaptive to the data. The presented technique has been successfully evaluated and compared with DCT and DWT based watermarking methods. Experimental results show robust performance of the PCA based method against most prominent attacks.

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