Images are inherently affected by different noises such as, speckle, salt and pepper, Gaussian, poisson, and white noise during its acquisition or transmission, hence, their true intensities cannot be reflected from the pixel values of an image. The main focus of this work is on designing a filtering method that preserves the edges of an image while removing the noise. The modified wiener filter is proposed to denoise satellite images. A detailed study on different noises and the filtering techniques, such as mean, median, wiener, Gaussian filter and the proposed modified wiener filter is done. The performance of these filtering methods is assessed by the image quality metrics, such as mean squared error, peak signal to noise ratio, and correlation coefficient. The results show the choice of a filter for denoising depends on the type of noise present in the image. The proposed modified wiener filter performs relatively well for most of the noise models compared with the existing linear and non-linear filtering methods. This technique can be widely used during the pre-processing of satellite images in remote sensing applications.