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Identification Type of Noise in Gray Scale Images using Wavelet-Network (WN) | ||
| Journal of Engineering | ||
| Article 1, Volume 11, Issue 1, 2005, Pages 203-211 | ||
| Authors | ||
| H. H. Khalil; W. A. Mahmoud | ||
| Abstract | ||
| 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. | ||
| Keywords | ||
| Wavelet Networks; Wavelet Transform; outlier; Function approximation | ||
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