REMOVING IMAGE NOISE BASED ON FUZZY LOGIC CONCEPT

In the present research algorithms employing fuzzy logic on median and mean filters for improving impulse noise removal performance for image processing have been developed. these algorithms can achieve significantly better image quality and capable of preserving the intricate details of the image than classical arithmetic and mean filters when the images are corrupted by impulse noise.the proposed fuzzy image filters (filter1, filter2 and filter3) are based on a combination of fuzzy impulse detection and restoration of corrupted pixels. fuzzy knowledge base required for detection of impulses.the research also presents an adaptive fuzzy filter system (filter 4) for noisy image enhancement combining smoothing and sharpening. the method is automatically obtaining an optimum parameter value adaptively by evaluating the local features. we present the results for different levels of impulse noise corruption on several real images, and the performance of our proposed filters is compared with statistical noise removal methods to show the effectiveness of the proposed techniques.