Kronecker product approximations for image restoration with anti-reflective boundary conditions

31Citations
Citations of this article
7Readers
Mendeley users who have this article in their library.
Get full text

Abstract

The anti-reflective boundary condition for image restoration was recently introduced as a mathematically desirable alternative to other boundary conditions presently represented in the literature. It has been shown that, given a centrally symmetric point spread function (PSF), this boundary condition gives rise to a structured blurring matrix, a submatrix of which can be diagonalized by the discrete sine transform (DST), leading to an O(n2 log n) solution algorithm for an image of size n × n. In this paper, we obtain a Kronecker product approximation of the general structured blurring matrix that arises under this boundary condition, regardless of symmetry properties of the PSF. We then demonstrate the usefulness and efficiency of our approximation in an SVD-based restoration algorithm, the computational cost of which would otherwise be prohibitive. Copyright © 2005 John Wiley & Sons, Ltd.

Cite

CITATION STYLE

APA

Perrone, L. (2006). Kronecker product approximations for image restoration with anti-reflective boundary conditions. Numerical Linear Algebra with Applications, 13(1), 1–22. https://doi.org/10.1002/nla.458

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free