Image restoration is known as enhancement and recovery of images. Personal pictures captured by varied digital cameras will simply be manipulated by a range of dedicated image process algorithms .The aim of this paper is to implement a model of neural network with Filling-in technique to resolve the problem of image restoration, which is retrieving the original image degraded by invariant blur. The algorithm is proposed in this paper implements a general RBF neural network model with Probabilistic approach which differentiates the pixels of image according to their level of corruption and employees different ways to correct it. Less corrupted are corrected by remaining part of pixel using Filling-in technique, while others are corrected by using RBF neural network image restoration resulting in better signal to blur noise and better visual quality.
DOI: 10.17762/ijritcc2321-8169.15026
