A genetic algorithm for the identification and segmentation of known motion-blurred objects
ACS'09 Proceedings of the 9th WSEAS international conference on Applied computer science
PSF-Constraints based iterative blind deconvolution method for image deblurring
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
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Image deblurring and denoising are the main steps in early vision problems. A common problem in deblurring is the ringing artifacts created by trying to restore the unknown point spread function (PSF). The random noise present makes this task even harder. Variational blind deconvolution methods add a smoothness term for the PSF as well as for the unknown image. These methods can amplify the outliers correspond to noisy pixels. To remedy these problems we propose the addition of a first order reaction term which penalizes the deviation in gradients. This reduces the ringing artifact in blind image deconvolution. Numerical results show the effectiveness of this additional term in various blind and semi-blind image deblurring and denoising problems.