Image enhancement using artificial neural network and fuzzy logic
Shweta Narnaware, Roshni S. Khedgaonkar · 2015
Digital images are important source of information used for analysis and interpretation. During image acquisition image is degraded up to some extent. Thus we have to go through the process called image enhancement. It improves the visual appearance of an image. This paper presents a technique for image enhancement using artificial neural network and fuzzy logic. It denoise and enhance an image when it is corrupted by different noises such as salt and pepper, gaussian and non-gaussian noises. In Image analysis, denoising and enhancing are most important pre-processing and post-processing steps. Several filters have been illustrated till date but have many limitations. In the proposed technique, Artificial neural network determines type of noises whereas Fuzzy logic used for denoising and enhancement purpose. Experimental results shows the effectiveness of the proposed method by quantitative analysis and visual illustration. Several parameters like PSNR, MSE, AD, NAE are used for performance evaluation.