SURE-LET image deconvolution using multiple Wiener filters
Journal
Proceedings - International Conference on Image Processing, ICIP
ISBN
9781467325332
Date Issued
2012-12-01
Author(s)
Abstract
We propose a novel deconvolution algorithm based on the minimization of Stein's unbiased risk estimate (SURE). We linearly parametrize the deconvolution process by using multiple Wiener filterings as elementary functions, followed by undecimated Haar-wavelet thresholding. The key contributions of our approach are: 1) the linear combination of several Wiener filters with different (but fixed) regularization parameters, which avoids the manual adjustment of a single nonlinear parameter; 2) the use of linear parameterization, which makes the SURE minimization finally boil down to solving a linear system of equations, leading to a very fast and exact optimization of the whole deconvolution process. The results obtained on standard test images show that our algorithm favorably compares with the other state-of-the-art deconvolution methods in both speed and quality. © 2012 IEEE.
Subjects
Deconvolution | linear parametrization | SURE minimization | undecimated Haar wavelet thresholding | Wiener filtering
Type
conference paper