Alkhaldi, N. and Winkler, J.R. (2015) Blind image deconvolution using the Sylvester resultant matrix. In: 2015 IEEE International Conference on Image Processing (ICIP). IEEE International Conference on Image Processing, 27-30 Sep 2015, Quebec City, Canada. IEEE , pp. 784-788.
Abstract
This paper uses techniques from computational algebraic geometry to perform blind image deconvolution, such that prior knowledge of the point spread function (PSF) is not required to compute a deblurred form of a given blurred image. In particular, it is shown that the Sylvester resultant matrix enables the PSF to be calculated by two approximate greatest common divisor computations. These computations, and not greatest common divisor computations, are required because of the noise that is present in the exact image and PSF. The computed PSF is then deconvolved from the blurred image in order to calculate the deblurred image. The experimental results show consistently good results for the deblurred image and PSF, and they are compared with the results from other methods for blind image deconvolution.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Computer Science (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 16 Feb 2016 12:20 |
Last Modified: | 15 Mar 2016 15:09 |
Published Version: | http://dx.doi.org/10.1109/ICIP.2015.7350906 |
Status: | Published |
Publisher: | IEEE |
Refereed: | Yes |
Identification Number: | 10.1109/ICIP.2015.7350906 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:94319 |