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Author Katkovnik, Vladimir ♦ Paliy, Dmitriy ♦ Egiazarian, Karen ♦ Astola, Jaakko
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Lpa-ici Algorithm ♦ Frequency Domain ♦ Con Dence Interval ♦ Noisy Image ♦ Energy Criterion ♦ Deconvolu-tion Technique ♦ Simulation Experiment ♦ Novel Method ♦ Anisotropic Spatially-adaptive Denoising ♦ Recursive Gradient-projection Algorithm ♦ Window Size ♦ Blur Operator ♦ Good Performance ♦ Local Polynomial Approxima-tion
Description In this paper we present a novel method for multiframe blind deblurring of noisy images. It is based on minimization of the energy criterion produced in the frequency domain us-ing a recursive gradient-projection algorithm. For ltering and regularization we use the local polynomial approxima-tion (LPA) of both the image and blur operators, and para-digm of the intersection of con dence intervals (ICI) applied for selection adaptively varying scales (window sizes) of LPA. The LPA-ICI algorithm is nonlinear and spatially-adaptive with respect to the smoothness and irregularities of the im-age and blur operators. Simulation experiments demonstrate e ¢ ciency and good performance of the proposed deconvolu-tion technique. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2006-01-01
Publisher Institution EUSIPCO Proc. 14th European Signal Process. Conf