Title :
Image enhancement using artificial neural network and fuzzy logic
Author :
Narnaware, Shweta ; Khedgaonkar, Roshni
Author_Institution :
Dept. of Comput. Technol., YCCE, Nagpur, India
Abstract :
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.
Keywords :
fuzzy logic; fuzzy set theory; image denoising; image enhancement; neural nets; artificial neural network; fuzzy logic; image acquisition; image analysis; image denoising; image enhancement; quantitative analysis; visual illustration; Artificial neural networks; Conferences; Fuzzy logic; Image enhancement; Noise; AD; ANN; Fuzzy Logic; MSE; NAE; NK;
Conference_Titel :
Innovations in Information, Embedded and Communication Systems (ICIIECS), 2015 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-6817-6
DOI :
10.1109/ICIIECS.2015.7193203