Introduction - If you have any usage issues, please Google them yourself
In this paper, a new scaling-based image-adaptive
watermarking system has been presented, which exploits human
visual model for adapting the watermark data to local properties
of the host image. Its improved robustness is due to embedding
in the low-frequency wavelet coefficients and optimal control of
its strength factor HVS point of view. Maximum-likelihood
(ML) decoder is used aided by the channel side information. The
performance of the proposed scheme is analytically calculated
and verified by simulation. Experimental results confirm the
imperceptibility of the proposed method and its higher robustness
against attacks compared to alternative watermarking methods in
the literature