Impulsive Noise Suppression Methods Based on Time Adaptive Self-Organizing Map

Removal of noise and restoration images has been one the most interesting topics in field image processing past few years. Existing filter-based methods can remove noise; however, they cannot preserve quality information such as lines edges. In this article, various classifiers spatial filters are combined to achieve desirable restoration. Meanwhile, time adaptive self-organizing map (TASOM) classifier is more emphasized our feature extraction dimensionality reduction approaches details during process, restore from noise. The TASOM was compared with (SOM) network, a suitable method for attempted. As result, we achieved an optimum reduce impulsive addition, by using neural better suppression achieved. Experimental results show that proposed effectively removes impulse maintains color well details.