Edge Testing of Noisy Image Based on Wavelet Neural Network

Abstract

To perfect inspecting effectiveness for image edge with noise, wavelet neural network is used for executing inspection of image edge. Basic theory of image noise is analyzed firstly. Secondly, the basic theory of wavelet neural network is analyzed, and framework of wavelet neural network is designed. Thirdly, a improved genetic algorithm is designed to carry out optimization for the parameters of wavelet neural network, finally numerical analysis on testing for image edge concluding noise is implemented, analysis results illustrate that the proposed model is an effective tool for testing the edge of image concluding noise.