Abstract-A watermarking algorithm operating in the wavelet domain is presented. Performance improvement with respect to existing algorithms is obtained by means of a new approach to mask the watermark according to the characteristics of the human visual system (HVS). In contrast to conventional methods operating in the wavelet domain, masking is accomplished pixel by pixel by taking into account the texture and the luminance content of all the image subbands. The watermark consists of a pseudorandom sequence which is adaptively added to the largest detail bands. As usual, the watermark is detected by computing the correlation between the watermarked coefficients and the watermarking code, anyway the detection threshold is chosen in such a way that the knowledge of the watermark energy used in the embedding phase is not needed, thus permitting to adapt it to the image at hand. Experimental results and comparisons with other techniques operating in the wavelet domain prove the effectiveness of the new algorithm.Index Terms-Image watermarking, perceptual noise masking, wavelets.

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Watermark detection, i.e., the detection of an invisible signal hidden within an image for copyright protection or data authentication, has classically been tackled by means of correlation-based techniques. Nevertheless, when watermark embedding does not obey an additive rule, or when the features the watermark is superimposed on do not follow a Gaussian pdf, correlation-based decoding is not the optimum choice. A new decoding algorithm is presented here which is optimum for nonadditive watermarks embedded in the magnitude of a set of full-frame DFT coefficients of the host image. By relying on statistical decision theory, the structure of the optimum is derived according to the Neyman-Pearson criterion, thus permitting to minimize the missed detection probability subject to a given false detection rate. The validity of the optimum decoder has been tested thoroughly to assess the improvement it permits to achieve from a robustness perspective. The results we obtained confirm the superiority of the novel algorithm with respect to classical correlation-based decoding.

In the field of image watermarking, research has been mainly focused on grayscale image watermarking, whereas the extension to the color case is usually accomplished by marking the image luminance, or by processing each color channel separately. A DCT domain watermarking technique expressly designed to exploit the peculiarities of color images is presented. The watermark is hidden within the data by modifying a subset of full-frame DCT coefficients of each color channel. Detection is based on a global correlation measure which is computed by taking into account the information conveyed by the three color channels as well as their interdependency. To ultimately decide whether or not the image contains the watermark, the correlation value is compared to a threshold. With respect to existing grayscale algorithms, a new approach to threshold selection is proposed, which permits reducing the probability of missed detection to a minimum, while ensuring a given false detection probability. Experimental results, as well as theoretical analysis, are presented to demonstrate the validity of the new approach with respect to algorithms operating on image luminance onl