Detection from noisy images by using the fuzzy technique

When edges are to be extracted from an image signal with superposed impulsive additive noises, the noise must be eliminated beforehand. In other words, two independent processing operations must be executed, in the order of noise elimination and edge detection. The elimination of the impulsive noise naturally degrades the edges of the original signal. Consequently, noise elimination and edge detection should be executed in connection with each other. This study tries to realize a new edge detector method, which includes both impulsive noise elimination and edge detection by using fuzzy inference. In the proposed method, the extent of edge detection and the extent of noise elimination can be adjusted continuously by varying the setting of the membership function for the fuzzy inference. This paper presents a detailed guide for setting the membership function through several applied examples and demonstrates the usefulness of the approach. (C) 1999 Scripta Technica.