title: Blind image deconvolution through support vector regression.
abstract: 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.
authors.forename: Dalong
authors.initials: D
authors.lastname: Li
authors.forename: Russell M
authors.initials: RM
authors.lastname: Mersereau
authors.forename: Steven
authors.initials: S
authors.lastname: Simske
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003198:Computer Simulation; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016247:Information Storage and Retrieval / Q000379:methods*; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated / Q000379:methods*; D012044:Regression Analysis