Abstract: The search for efficient image de-noising methods still is a valid challenge at the crossing of functional analysis and statistics. In spite of the sophistication of the recently proposed methods most algorithms have not yet attained a desirable level of applicability. In this study, a hybrid denoising method is proposed to find the best possible solutions, so that, PSNR (Peak Signal Noise-to-Ratio) value of the image after denoising process is optimal. The proposed model is based on morphologic filter which has been successfully used in noise removal and hybrid with proposed mathematical algorithm which exploits the potential features of both morphologic filter and mathematical algorithm at the same time their limitations are overcome. Three types of noise inserted on colored image and then removed by suggested filters to check the relation between the noise type and noise removing methods. The types of noise amplifier noise (Gaussian noise), salt and pepper noise, speckle noise. The quality performance of these methods was checked by visual checking of the resultant images and determining the PSNR value.