DIMINISHING NOISE USING ADAPTIVE FUZZY SWITCHING MEDIAN FILTER

This research work presents a simple, yet efficient way to remove noise from d igital images. The method comprises three phases: the first phase is to detect the noise in the image. In this phase, based on only the intensity values, the pixels are roughly divided into two classes, which are “noise - free pixel” and “noise pixel”. Then, the second phase is to remove the impulse noise from the image. In this phase, only the “noise - pixels” are processed. The “noise free pixels” are copied directly to the output image. Then, the third phase, in which adaptive fuzzy inference system is used for giving the choice to the user. In this research paper, present a novel method for the removal of noise from digital images. The proposed operator is a hybrid filter obtained by appropriately combining a low, median and high pass filter and adaptive fuz zy switching median filter. The noise is exactly estimated through the proposed operator. The distinctive feature of the proposed operator is that it offers well line, edge, detail and texture preservation performance while, at the same time, effectively r emoving noise from the input image. AFSM filter is capable of removing all kind of noise. The internal parameters of the FIS are adaptively optimized by training. This proposed method is suitable to be implemented in consumer electronics products such as d igital televisions, cameras, etc.