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A hybrid method for image Denoising based on Wavelet Thresholding and RBF network

Author(s): Sandeep dubey | Fehreen hasan | Gaurav Shrivastava

Journal: International Journal of Advanced Computer Research
ISSN 2249-7277

Volume: 2;
Issue: 2;
Start page: 167;
Date: 2012;
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Keywords: Image denoising | Wavelet thresholding | RBF

Digital image denoising is crucial part of image preprocessing.The application of denoising process insatellite image data and also in televisionbroadcasting. Image data sets collected by imagesensors are generally contaminated by noise.Imperfect instruments, problems with the dataacquisition process, and interfering naturalphenomena can all degrade the data of interest.Furthermore, noise can be introduced by transmissionerrors and compression. Thus, denoising is often anecessary and the first step to be taken before theimages data is analyzed. In this paper we proposed anovel methodology for image denoising. Imagedenoising method based on wavelet transform andradial basis neural network and also used concept ofsoft thresholding. Wavelet transform decomposedimage in to different layers, the decomposed layerdifferentiate by horizontal, vertical and diagonal. Forthe test of our hybrid method, we used noise imagedataset. This data provided by UCI machine learningwebsite. Our proposed method compare withtraditional method and our base paper method andgetting better comparative result.
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