Noise Reduction Technique for Images using Radial Basis Function Neural Networks

Autor:	Sander Ali Khowaja, Syed Zafi Sherhan Shah, Muhammad Usman Memon
Jazyk:	angličtina
Rok vydání:	2014
Předmět:	Image Processing Noise Reduction Neural Networks Radial Basis Function Technology Engineering (General). Civil engineering (General) TA1-2040 Science
Zdroj:	Mehran University Research Journal of Engineering and Technology, Vol 33, Iss 3, Pp 278-285 (2014)
Druh dokumentu:	article
ISSN:	0254-7821 2413-7219
Popis:	This paper presents a NN (Neural Network) based model for reducing the noise from images. This is a RBF (Radial Basis Function) network which is used to reduce the effect of noise and blurring from the captured images. The proposed network calculates the mean MSE (Mean Square Error) and PSNR (Peak Signal to Noise Ratio) of the noisy images. The proposed network has also been successfully applied to medical images. The performance of the trained RBF network has been compared with the MLP (Multilayer Perceptron) Network and it has been demonstrated that the performance of the RBF network is better than the MLP network.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/77a756c68a9547d2a5d0d445deecdc76 Zobrazit plný text záznamu View record in DOAJ