Performances of iterative blind deconvolution methods for motion-blurred images are usually reduced depending on the accuracy of the required initial guess of the blur. We examine this dependency, and a two-stage restoration procedure is proposed: First we perform a direct technique with a single straightforward process to produce a rough initial estimate of the blur, and then an iterative technique is employed to refine the blur estimate. Two common iterative techniques (the expectation-maximization and the Richardson–Lucy methods) are examined here and implemented in the combined direct–iterative modification for a variety of motion blur types. Results show that the combined method significantly improves the reliability of the deconvolution process.
© 2006 Optical Society of America
Original Manuscript: September 12, 2005
Revised Manuscript: October 31, 2005
Manuscript Accepted: November 6, 2005
Vadim Loyev and Yitzhak Yitzhaky, "Initialization of iterative parametric algorithms for blind deconvolution of motion-blurred images," Appl. Opt. 45, 2444-2452 (2006)