(Publisher of Peer Reviewed Open Access Journals)

International Journal of Advanced Computer Research (IJACR)

ISSN (Print):2249-7277    ISSN (Online):2277-7970
Volume-2 Issue-4 June-2012
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Paper Title : A hybrid method for image Denoising based on Wavelet Thresholding and RBF network
Author Name : Sandeep Dubey, Fehreen Hasan, Gaurav Shrivastava
Abstract :

Digital image denoising is crucial part of image pre-processing. The application of denoising process in satellite image data and also in television broadcasting. Image data sets collected by image sensors are generally contaminated by noise. Imperfect instruments, problems with the data acquisition process, and interfering natural phenomena can all degrade the data of interest. Furthermore, noise can be introduced by transmission errors and compression. Thus, denoising is often a necessary and the first step to be taken before the images data is analyzed. In this paper we proposed a novel methodology for image denoising. Image denoising method based on wavelet transform and radial basis neural network and also used concept of soft thresholding. Wavelet transform decomposed image in to different layers, the decomposed layer differentiate by horizontal, vertical and diagonal. For the test of our hybrid method, we used noise image dataset. This data provided by UCI machine learning website. Our proposed method compare with traditional method and our base paper method and getting better comparative result.

Keywords : Image denoising, Wavelet thresholding, RBF.
Cite this article : Sandeep Dubey, Fehreen Hasan, Gaurav Shrivastava, " A hybrid method for image Denoising based on Wavelet Thresholding and RBF network " , International Journal of Advanced Computer Research (IJACR), Volume-2, Issue-4, June-2012 ,pp.167-172.