IEEE Trans Image Process - Adaptive multiwavelet-based watermarking through JPW masking.

Tópicos

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Resumo

In this paper, a multibit, multiplicative, spread spectrum watermarking using the discrete multiwavelet (including unbalanced and balanced multiwavelet) transform is presented. Performance improvement with respect to existing algorithm is obtained by means of a new just perceptual weighting (JPW) model. The new model incorporates various masking effects of human visual perception by taking into account the eye's sensitivity to noise changes depending on spatial frequency, luminance and texture of all the image subbands. In contrast to conventional JND threshold model, JPW describing minimum perceptual sensitivity weighting to noise changes, is fitter for nonadditive watermarking. Specifically, watermarking strength is adaptively adjusted to obtain minimum perceptual distortion by employing the JPW model. Correspondingly, an adaptive optimum decoding is derived using a statistic model based on generalized-Gaussian distribution (GGD) for multiwavelet coefficients of the cover-image. Furthermore, the impact of multiwavelet characteristics on proposed watermarking scheme is also analyzed. Finally, the experimental results show that proposed JPW model can improve the quality of the watermarked image and give more robustness of the watermark as compared with a variety of state-of-the-art algorithms.

Resumo Limpo

paper multibit multipl spread spectrum watermark use discret multiwavelet includ unbalanc balanc multiwavelet transform present perform improv respect exist algorithm obtain mean new just perceptu weight jpw model new model incorpor various mask effect human visual percept take account eye sensit nois chang depend spatial frequenc lumin textur imag subband contrast convent jnd threshold model jpw describ minimum perceptu sensit weight nois chang fitter nonaddit watermark specif watermark strength adapt adjust obtain minimum perceptu distort employ jpw model correspond adapt optimum decod deriv use statist model base generalizedgaussian distribut ggd multiwavelet coeffici coverimag furthermor impact multiwavelet characterist propos watermark scheme also analyz final experiment result show propos jpw model can improv qualiti watermark imag give robust watermark compar varieti stateoftheart algorithm

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