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External Filtering and Wavelet Domain Thresholding-based Denoising Method for AWGN corrupted imagesExternal Filtering and Wavelet Domain Thresholding-based Denoising Method for AWGN corrupted images

Sumit Singh Parihar, Shailesh Khaparkar


In this work an image de-noising method with external bilateral filtering and wavelet domain thresholding has been proposed. In Gaussian filtering, it fails to denoise an image at edges where the spatial variations are not smooth and causesblurs at the edges in the image. External bilateral filter (EBF) beats this by filtering the picture in both reach and area (space). Respective separating is a nearby, nonlinear and non-iterative procedure which thinks about both dim level (shading) likenesses and mathematical closeness of the adjoining pixels. With bilateral filter, the approximation sub-band results in loss of some image details, whereas that after each level of wavelet reconstruction flattens the gray levels causing anunpleasing output image. To overcome the above issue, extension of bilateral filtering with introduction of wavelets for thresholding has been proposed. Instead of direct filtering or direct wavelet domainthresholding of noisy image, the proposed method first obtains the filtered version of image using bilateral filtering and then this filtered version of image undergoes to wavelet domain thresholding using Bayes-shrink rules. In this approach the advantages of both the methods are achieved. To check the effectiveness of the proposed method in image denoising, we have compared the results with recent image denoising methods.



Gaussian noise, image denoising, filter banks and thresholding, bilateral filtering, discrete wavelet domain thresholding

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