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Proceedings Paper

Maximum-likelihood blur identification
Author(s): Reginald L. Lagendijk; Jan Biemond
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Paper Abstract

In this paper we discuss the use of maximum likelihood estimation procedures for the identification of unknowns blur from a blurred image. The main focus will be on the problem of estimating the coefficients of relatively large point-spread functions, and the estimation of the support size of point-spread functions in general. Two improved blur identification techniques are proposed which are both based on the expectation- maximization algorithm. In the first method we describe the point-spread function by a parametric model, while in the second method resolution pyramids are employed to identify the point-spread function in a hierarchical manner.

Paper Details

Date Published: 1 September 1990
PDF: 12 pages
Proc. SPIE 1360, Visual Communications and Image Processing '90: Fifth in a Series, (1 September 1990); doi: 10.1117/12.24150
Show Author Affiliations
Reginald L. Lagendijk, Delft Univ. of Technology (Netherlands)
Jan Biemond, Delft Univ. of Technology (Netherlands)

Published in SPIE Proceedings Vol. 1360:
Visual Communications and Image Processing '90: Fifth in a Series
Murat Kunt, Editor(s)

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