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Blind Poissonian images deconvolution with framelet regularization |
Optics Letters, Vol. 38, Issue 4, pp. 389-391 (2013)
http://dx.doi.org/10.1364/OL.38.000389
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Abstract
We propose a maximum a posteriori blind Poissonian images deconvolution approach with framelet regularization for the image and total variation (TV) regularization for the point spread function. Compared with the TV based methods, our algorithm not only suppresses noise effectively but also recovers edges and detailed information. Moreover, the split Bregman method is exploited to solve the resulting minimization problem. Comparative results on both simulated and real images are reported.
© 2013 Optical Society of America
OCIS Codes
(100.1830) Image processing : Deconvolution
(100.2000) Image processing : Digital image processing
(100.3020) Image processing : Image reconstruction-restoration
(100.1455) Image processing : Blind deconvolution
ToC Category:
Image Processing
History
Original Manuscript: December 4, 2012
Revised Manuscript: January 2, 2013
Manuscript Accepted: January 2, 2013
Published: February 6, 2013
Citation
Houzhang Fang, Luxin Yan, Hai Liu, and Yi Chang, "Blind Poissonian images deconvolution with framelet regularization," Opt. Lett. 38, 389-391 (2013)
http://www.opticsinfobase.org/ol/abstract.cfm?URI=ol-38-4-389
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