Image Enhancement Using Adaptive Neuro-Fuzzy Inference System

This paper presents a hybrid filter for denoising and enhancing digital image in situation where the image is corrupted by salt and pepper noise. Image denoising and enhancement are important preprocessing and post processing steps in image analysis. Successful results of image analysis extremely depend on image enhancement. There are several filters have been illustrated till date. But they are highly sensitive to noise. The structure of the proposed hybrid filter, to make the process robust against noise, is a combination of nonlinear switching median filter and neuro-fuzzy network. The internal parameters of the neuro-fuzzy network are adaptively optimized by training. The most distinctive feature of the proposed operator offers excellent line, edge, and fine detail preservation performance while, at the same time, effectively removing noise from the input image. The proposed filter is evaluated under different noisy condition on several test images and also compared with already existing filters for performance evaluation.