A novel visible watermarking algorithm based on noise reduction and Human Visible System (HVS) model approach is presented in this study. In order to get the best tradeoff between the embedding energy of watermark and the perceptual translucence for visible watermark, the composite coefficients using global and local characteristics of the host image in the discrete wavelet transform (DWT) domain is considered. The application of the perceptual model of contrast-sensitive function (CSF) with the noise reduction of the visibility thresholds for HVS in DWT domain achieves the goal of fine tuning of the perceptual weights according to the basis function amplitudes for the best quality of perceptual translucence. Instead of three types of block classification- textures, edges and smooth areas, the computation of Noise Visibility Function (NVF) characterizes the local image properties to determine the optimal watermark locations and strength at the watermark embedding stage. The experimental results demonstrate that the proposed technique improves the PSNR values and visual quality than the CSF only based algorithms.