These days the concept of denoising is not restricted to the field of photography or publication where image needs to be improved for printing purpose. It is quite useful tool in number of digital image processing application such as space exploration where noise can be introduced due to artifacts generated by mechanical or optical system of a telescope. Image denoising finds application in field of medical science where high quality images are required in the form of x-ray images, ultrasound and city scan images. A good quality medical image can be useful to diagnose diseases. In the field of forensic science, where evidence sometimes is available in extremely bad quality, in such case, denoising tools are used to produce quality images. Moreover core digital image processing applications like text extraction from images, number plate detection, OCR etc. use denoising as a pre-processing tool. Removing noising from digital images is still a challenging task. There are various methods available in literature but not a single method is suitable for all type of image noises. In this paper, we have discussed various algorithms with assumptions, advantages and disadvantages. The comparative analysis of these noising techniques is carried out to find the most suitable and reliable method for image denoising.