Maximum-likelihood blur identification

Reginald L. Lagendijk; Jan Biemond

doi:10.1117/12.24150

1 September 1990 Maximum-likelihood blur identification

Reginald L. Lagendijk, Jan Biemond

Proceedings Volume 1360, Visual Communications and Image Processing '90: Fifth in a Series; (1990) https://doi.org/10.1117/12.24150
Event: Visual Communications and Image Processing '90, 1990, Lausanne, Switzerland

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.

Citation Download Citation

Reginald L. Lagendijk and Jan Biemond "Maximum-likelihood blur identification", Proc. SPIE 1360, Visual Communications and Image Processing '90: Fifth in a Series, (1 September 1990); https://doi.org/10.1117/12.24150

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