While capturing, processing, transmitting and reproducing, images are frequently affected by noise. A primary goal of image processing is to restore the original image after the noise has been removed. Without previous understanding of the noise model, removing noise from digital pictures or documents is extremely challenging job. As a result, while studying picture de-noising algorithms, a review of noise models is necessary. We present a quick review of several noise models in this work. We can assume that the noise model is spatial invariant that is not dependent of spatial location. We offer a comprehensive and quantitative study of noise models in digital images. To enhance the quality of images by removing various types of noise, a number of filtering techniques are used.

Keywords- Gaussian noise, Exponential noise, Rayleigh noise, Speckle noise, Erlang noise, Probability density function (PDF)