Identification type of noise in gray scale images using wavelet-network (WN)‎

Abstract EN

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.