Rakesh Kumar and B
نویسندگان
چکیده
Wavelet thresholding is a signal estimation technique that exploits the capabilities of wavelet transform for signal denoising. But the choice of thresholding function has restricted there wide spread use in image denoising application. In this paper we proposed a computationally more efficient thresholding scheme by incorporating the neighbouring wavelet coefficients, with different threshold value for different sub bands, it is based on generalized Gaussian Distribution (GGD) modeling of sub band coefficients. In this proposed method, the choice of the threshold estimation is carried out by analyzing the statistical parameters of the wavelet sub band coefficients like standard deviation, arithmetic mean and geometrical mean. It is demonstrated that our proposed method performs better than: VisuShrink, Normalshrink and NeighShrink algorithms in terms of PSNR ratio. KeywordsImage denoising, Gaussian Noise, Filter Banks and threshold, Wavelet domain and, Neighbouring coefficients.
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تاریخ انتشار 2010