Filtration Based Noise Reduction Technique in an Image

Image transmission is a process that is performed in all kind of multimedia systems such as space crafts and cellular phones. When an image is inputted for broadcasting, it doesn't contain that much of quality after transmission as original image was having. Noise is the main factor that can contaminate the final image in distinct ways like transmission through air or decompression noise after compressed data that is stored. The final image can be degraded because of this. To resolve the issue of degradation, different filtering steps can be applied or preprocessing can be done. Lots of noise suppression filters have been designed to reduce the degradation in the appeared image after transmission. Different filtration techniques are used to overcome this problem. But image may be blurred after filtration. Median filtration yields best results is such a way that image won't be blurred after transmission. In this paper, we present a filtration technique to decrease noise in a transformed image with the help of cellular automata concept. Our model of CA works for reducing two kind noises in resultant image. First is salt and pepper noise and second is gaussain noise. Our proposed model reduces these noises effectively as compared to other models.