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-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