The process of removing noise from the original image is still a demanding problem for researchers. There have been several algorithms and each has its assumptions, merits, and demerits. The prime focus of this paper is related to the pre processing of an image before it can be used in applications. The pre processing is done by de-noising of images. In order to achieve these de-noising algorithms, filtering approach and wavelet based approach are used and performs their comparative study. Different noises such as Gaussian noise, salt and pepper noise, speckle noise are used. The filtering approach has been proved to be the best when the image is corrupted with salt and pepper noise. The wavelet based approach has been proved to be the best in de-noising images corrupted with Gaussian noise. A quantitative measure of comparison is provided by the parameters like Peak signal to noise ratio, Root mean square error and Correlation of the image.
