Noise reduction technique for images using radial basis function neural networks.

Sander Ali Khowaja; Syed Zafi Sherhan Shah; Muhammad Usman Memon

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Noise reduction technique for images using radial basis function neural networks.

Author(s)

Sander Ali Khowaja Institute of Information & Communication Technology, University of Sindh, Jamshoro, Pakistan

Syed Zafi Sherhan Shah Department of Telecommunication Engineering, Mehran University of Engineering & Technology, Jamshoro, Pakistan

Muhammad Usman Memon Department Of Telecommunication Engineering, Institute Of Business Administration Sukkur, Pakistan

Abstract

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.

Publication Details

Page(s) 278-285

DOI DOI not available

Published Journal: Mehran University Research Journal of Engineering and Technology, Volume: 33, Issue: 3, Year: 2014

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