Image Restoration by blind deconvolution
نویسندگان
چکیده
In this Diploma Thesis we will present some methods to improve the quality of a given pictures. In particular blind deconvolution will be applied to deblurr the images. The deconvolution tries to invert the blurring of an image that is modeled by the convolution g = f ∗ h. Blind deconvolution tries to do this without knowledge of the point spread function that blurred the image. In the Thesis first the depredation model is described as well as problems that have to be addressed when applying deconvolution i.e. the extreme ill posedness of the deconvolution and the singularity of the blind deconvolution. A method of inverse filtering is presented, the NASRIF by Deepa Kundur and a more promising approach using total variation (TV) and Tikhonov (TK) regularization is shown. Numerical experiments presented in this thesis show that it is beneficial to use TV on f but TK regularization on the point spread function h rather then using TV on both or TK on both as done in previous publications. The reader can easily reproduce the experiments that lead to this conclusion by using the Matlab-GUI attached to this document. At the end it is shown how to carry out the deblurring in physical space as well as in Fourier space. The best results can be achieved by restoring the image in Fourier space but the point spread function in physical space.
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