An adaptive algorithm for corrupted images

Noise is ever-present in communication channels and can produce devastating degradation to the images at the receiver end. In this paper, a novel approach to detecting different types of noise models in corrupted images is presented. Basically, it is a two-step process that has the ability to handle real-time applications due to its computational simplicity. The proposed algorithm handles error correction more efficiently in the second stage of processing, given a means to detect the type of noise present in the first stage. This algorithm will be verified and tested against existing methods on different noise models. Preliminary results show that this methodology can accurately detect and compensate for various noise sources common in multimedia applications, such as impulse, Gaussian, and uniform noise, with minimal loss to the integrity of the original digital image.