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Blind Image Deconvolution Through Support Vector Regression

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3 Author(s)
Li, D. ; Sch. of Electr. & Comput. Eng., Georgia Inst. of Technol., Atlanta, GA ; Mersereau, R.M. ; Simske, S.

This letter introduces a new algorithm for the restoration of a noisy blurred image based on the support vector regression (SVR). Experiments show that the performance of the SVR is very robust in blind image deconvolution where the types of blurs, point spread function (PSF) support, and noise level are all unknown

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Neural Networks, IEEE Transactions on  (Volume:18 ,  Issue: 3 )