IMAGE DE - BLURRING USING WIENER DE - CONVOLUTION AND WAVELET FOR DIFFERENT BLURRING KERNELJournal: International Journal of Engineering Sciences & Research Technology (IJESRT) (Vol.5, No. 6)
Publication Date: 2016-06-30
Authors : M.Tech Research Scholar Shuchi Singh; Asst Vipul Awasthi;
Page : 60-64
Keywords : Wavelet Transform (WT); Wiener;
Image de - convolution is an active research area of recovering a sharp image after blurring by a convolution. One of the problems in image de - convolution is how to preserve the texture structures while removing blur in presence of noise. Various methods hav e been used for such as gradient based methods, sparsity based methods, and nonlocal self - similarity methods. In this thesis , we have used the conventional non - blind method of Wiener de - convolution. Further Wavelet denoising has been used to improve the im age quality without det e oriating the fine structure of images. The method has been applied for different PSF and different images to validate the results of the de - blurring.
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Last modified: 2016-06-17 16:14:55