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Blur estimation in limited-control environments

We propose a method to estimate the blur of a fixed imaging system, without control of camera position or lighting, using an inexpensive target. Such a method is applicable, for example, in the restoration of surveillance imagery where the imaging system is available, but with only limited control of the imaging conditions. We extend a previously proposed parametric blur model and maximum likelihood technique to estimate a more general family of blur functions. The requirements for an appropriate characterization target are also discussed. Experimental results with artificial and real data are presented to validate the proposed approach.