IMAGE DE - BLURRING USING WIENER DE - CONVOLUTION AND WAVELET FOR DIFFERENT BLURRING KERNEL

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.