Kronecker product and SVD approximations for separable spatially variant blurs

Julie Kamm; James G. Nagy

doi:10.1117/12.325696

2 October 1998 Kronecker product and SVD approximations for separable spatially variant blurs

Julie Kamm, James G. Nagy

Proceedings Volume 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII; (1998) https://doi.org/10.1117/12.325696
Event: SPIE's International Symposium on Optical Science, Engineering, and Instrumentation, 1998, San Diego, CA, United States

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

Citation Download Citation

Julie Kamm and James G. Nagy "Kronecker product and SVD approximations for separable spatially variant blurs", Proc. SPIE 3461, Advanced Signal Processing Algorithms, Architectures, and Implementations VIII, (2 October 1998); https://doi.org/10.1117/12.325696

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