Making intelligent decisions on noisy images

Abstract

Making successful decisions on image classification can be influenced by the level of present noise. The noise on data can be reduced applying many classical and advanced techniques such as low pass filters or wavelets. However, in some cases the presence of the noise is not global but located only in some particular regions of the image. In these situations the application of global filters over the entire image is not a suitable option since the noise and the information are equally reduced. This article describes an intelligent approach to eliminate noise and avoid affecting the overall image.