Efficient Distortion Reduction of Mixed Noise Filters by Neuro-fuzzy Processing
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- Yüksel M.E., Baştürk A. (2006) Efficient Distortion Reduction of Mixed Noise Filters by Neuro-fuzzy Processing. In: Gabrys B., Howlett R.J., Jain L.C. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2006. Lecture Notes in Computer Science, vol 4252. Springer, Berlin, Heidelberg
A simple method for reducing undesirable distortion effects of mixed noise filters for digital images is presented. The method is based on a simple 2-input 1-output neuro-fuzzy network. The internal parameters of the neuro-fuzzy network are adaptively optimized by training. The training is easily accomplished by using simple artificial images generated on a computer. The method can be used with any type of mixed noise filters since its operation is completely independent of the filter. The proposed method is applied to two representative mixed noise filters from the literature under different noise conditions and image properties. Results indicate that the proposed method may efficiently be used with any type of mixed noise filters to effectively reduce their distortion effects.
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