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Design of Hybrid Filter for Denoising Images Using Fuzzy Network and Edge Detecting

In this paper, a novel method of hybrid filter for denoising digital images corrupted by mixed noise has been presented. The proposed design of hybrid filter utilizes the concept of neuro fuzzy network and spatial domain filtering. This method incorporates improved adaptive wiener filter and adaptive median filter to reduce white Gaussian noise and impulse noise respectively. Selection of filters depends upon the performance of the impulse noise detection process. The edge detector is capable of extracting edges from filtered images which has been blurred due to different filtering actions. Optimization of neuro fuzzy network training with its internal parameters is collectively accomplished with different natural and synthetic images. Data accomplished from the edge detector, noise filter with the corrupted image together form the training data set. The most distinctive feature of the proposed operator over most other operators is that it offers excellent line, edge, detail, and texture preservation performance while, at the same time, effectively removing noise from the input image.