Identification Type of Noise in Gray Scale Images using Wavelet-Network (WN)


In this paper, Wavelet-Network (WN) model has been recently proposed and applied to image processing, e.g., identification type of noise in Gray-Scale Images (GSI). This paper develops a new technique, which employs a Discrete Wavelet Transforma(DWT) and an Artificial Neural Network (ANN). This WN technique uses special mother wavelet ψ (x1, x2) of (DWT) as activation function for (ANN) instead of the traditional activation function like ( Log sigmoid, Tan sigmoid, . etc). it is shown here that the benefit of WN circuits which uses WN is a good approximation tool for GSI images. These approximation patterns for images forced ANN to learn on these images which will be used in the test phase after that.