Winkler, J.R. (2016) Polynomial computations for blind image deconvolution. Linear Algebra and Its Applications, 502. pp. 77-103. ISSN 0024-3795
Abstract
This paper considers the problem of blind image deconvolution (BID) when the blur arises from a spatially invariant point spread function (PSF) H, which implies that a blurred image G is formed by the convolution of H and the exact form F of G. Since the multiplication of two bivariate polynomials is performed by convolving their coefficient matrices, the equivalence of the formation of a blurred image and the product of two bivariate polynomials implies that BID can be performed by considering F, G and H to be bivariate polynomials on which polynomial operations are performed. These operations allow the PSF to be computed, which is then deconvolved from the blurred image G, thereby obtaining a deblurred image that is a good approximation of the exact image F. Computational results show that the deblurred image obtained using polynomial computations is better than the deblurred image obtained using other methods for blind image deconvolution.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2015 Elsevier Inc. All rights reserved. This is an author produced version of a paper subsequently published in Linear Algebra and its Applications. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Blind image deconvolution; Sylvester resultant matrix; Structured matrices |
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: | 03 Nov 2015 15:13 |
Last Modified: | 01 Nov 2016 22:24 |
Published Version: | http://dx.doi.org/10.1016/j.laa.2015.10.010 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.laa.2015.10.010 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:91315 |