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Edge Testing of Noisy Image Based on Wavelet Neural Network

Edge Testing of Noisy Image Based on Wavelet Neural Network 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, and the edge of images with Gaussian noise and Rayleigh noise is processed based on MATLAB software. The basic theory of wavelet neural network is analyzed, and framework of wavelet neural network is designed, the mathematical expressions of hidden layer are established. And an improved genetic algorithm is designed to carry out optimization for the parameters of wavelet neural network, the fitness degree function is established, and the analysis flowchart of algorithm is designed. 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Automatic Control and Computer Sciences Springer Journals

Edge Testing of Noisy Image Based on Wavelet Neural Network

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References (43)

Publisher
Springer Journals
Copyright
Copyright © Allerton Press, Inc. 2023. ISSN 0146-4116, Automatic Control and Computer Sciences, 2023, Vol. 57, No. 1, pp. 61–69. © Allerton Press, Inc., 2023.
ISSN
0146-4116
eISSN
1558-108X
DOI
10.3103/s014641162301011x
Publisher site
See Article on Publisher Site

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, and the edge of images with Gaussian noise and Rayleigh noise is processed based on MATLAB software. The basic theory of wavelet neural network is analyzed, and framework of wavelet neural network is designed, the mathematical expressions of hidden layer are established. And an improved genetic algorithm is designed to carry out optimization for the parameters of wavelet neural network, the fitness degree function is established, and the analysis flowchart of algorithm is designed. 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.

Journal

Automatic Control and Computer Sciences – Springer Journals

Published: Feb 1, 2023

Keywords: edge testing; noisy image; wavelet neural network

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