Title :
Sure-based blind Gaussian deconvolution
Author :
Xue, Feng ; Blu, Thierry
Author_Institution :
Dept. of Electron. Eng., Chinese Univ. of Hong Kong, Hong Kong, China
Abstract :
We propose a novel blind deconvolution method that consisting of firstly estimating the variance of the Gaussian blur, then performing non-blind deconvolution with the estimated PSF. The main contribution of this paper is the first step - to estimate the variance of the Gaussian blur, by minimizing a novel objective functional: an unbiased estimate of a blur MSE (SURE). The optimal parameter and blur variance are obtained by minimizing this criterion over linear processings that have the form of simple Wiener filterings. We then perform non-blind deconvolution using our recent high-quality SURE-based deconvolution algorithm. The very competitive results show the highly accurate estimation of the blur variance (compared to the ground-truth value) and the great potential of developing more powerful blind deconvolution algorithms based on the SURE-type principle.
Keywords :
Gaussian processes; Wiener filters; deconvolution; estimation theory; mean square error methods; Gaussian blur variance estimation; PSF estimation; SURE-based blind Gaussian deconvolution method; Wiener filtering; blur MSE; nonblind deconvolution; Approximation methods; Deconvolution; Estimation; Image processing; Minimization; Signal to noise ratio; Standards; Blind deconvolution; Wiener filtering; estimation of blur variance; minimization of blur SURE;
Conference_Titel :
Statistical Signal Processing Workshop (SSP), 2012 IEEE
Conference_Location :
Ann Arbor, MI
Print_ISBN :
978-1-4673-0182-4
Electronic_ISBN :
pending
DOI :
10.1109/SSP.2012.6319729