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Proceedings Paper

Kronecker product and SVD approximations for separable spatially variant blurs
Author(s): Julie Kamm; James G. Nagy
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Paper Abstract

In image restoration, a separable, spatially variant blurring function has the form k(x, y; s, 1) =ki(x,s)k2(y, t). If this kernel is known, then discretizations lead to a blurring matrix which is a Kronecker product of two matrices of smaller dimension. If k is not known precisely, such a discretization is not possible. In this paper we describe an interpolation scheme to construct a Kronecker product approximation to the blurring matrix from a set of observed point spread functions for separable, or nearly separable, spatially variant blurs. An approximate singular value decomposition is then computed from this Kronecker factorization.

Keywords: Image restoration, Interpolation, Kronecker product, space variant blur, SVD

Paper Details

Date Published: 2 October 1998
PDF: 12 pages
Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); doi: 10.1117/12.325696
Show Author Affiliations
Julie Kamm, Southern Methodist Univ. (United States)
James G. Nagy, Southern Methodist Univ. (United States)


Published in SPIE Proceedings Vol. 3461:
Advanced Signal Processing Algorithms, Architectures, and Implementations VIII
Franklin T. Luk, Editor(s)

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