Abstract

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

Comparison of direct blind deconvolution methods for motion-blurred images

Yitzhak Yitzhaky, Ruslan Milberg, Sergei Yohaev, and Norman S. Kopeika
Appl. Opt. 38(20) 4325-4332 (1999)

Multiframe blind deconvolution of heavily blurred astronomical images

Yulia V. Zhulina
Appl. Opt. 45(28) 7342-7352 (2006)

Parametric blind deconvolution: a robust method for the simultaneous estimation of image and blur

Joanne Markham and José-Angel Conchello
J. Opt. Soc. Am. A 16(10) 2377-2391 (1999)

Single channel blind image deconvolution from radially symmetric blur kernels

Kwang Eun Jang and Jong Chul Ye
Opt. Express 15(7) 3791-3803 (2007)

Iterative statistical approach to blind image deconvolution

Edmund Y. Lam and Joseph W. Goodman
J. Opt. Soc. Am. A 17(7) 1177-1184 (2000)