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Defocus blur parameters identification by histogram matching |
JOSA A, Vol. 29, Issue 8, pp. 1694-1706 (2012)
http://dx.doi.org/10.1364/JOSAA.29.001694
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Abstract
A defocus blur identification technique based on histogram analysis of a real edge image is presented. The image defocus process of a camera is formulated by incorporating the nonlinear camera response and the intensity-dependent noise model. The histogram matching between the synthesized and real defocused regions is then carried out with intensity-dependent filtering. By iteratively changing the point-spread function parameters, the best blur extent is identified from histogram comparison. We have performed the experiments on both the synthetic and real edge images. The results have demonstrated the robustness and feasibility of the proposed technique.
© 2012 Optical Society of America
OCIS Codes
(150.1135) Machine vision : Algorithms
(100.4995) Image processing : Pattern recognition, metrics
ToC Category:
Image Processing
History
Original Manuscript: October 17, 2011
Revised Manuscript: May 22, 2012
Manuscript Accepted: June 19, 2012
Published: July 27, 2012
Citation
Huei-Yung Lin and Xin-Han Chou, "Defocus blur parameters identification by histogram matching," J. Opt. Soc. Am. A 29, 1694-1706 (2012)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-29-8-1694
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