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Proceedings Paper

A new approach to blind PSF estimation based on Mallows' statistics Cp
Author(s): Feng Xue; Jiaqi Liu; Chenyang Mu; Min Zhao; Li Zhang; Shenghai Jiao
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Paper Abstract

We propose an unbiased estimator of the weighted mean squared error — Mallows’ statistics Cp — as a novel criterion for estimating a point spread function (PSF) from the degraded image only. The PSF is obtained by minimizing this new objective functional over a family of Wiener processings. Based on this estimated PSF, we then perform non-blind deconvolution using the popular BM3D algorithm. The Cp-based framework is exemplified with a number of parametric PSF’s, involving a scaling factor that controls the blur size. A typical example of such parametrization is the Gaussian kernel.

The experimental results demonstrate that the Cp-minimization yields highly accurate estimates of the PSF parameters, which also result in a negligible loss of visual quality, compared to that obtained with the exact PSF. The highly competitive results outline the great potential of developing more powerful blind deconvolution algorithms based on the Cp-estimator.


Paper Details

Date Published: 24 November 2014
PDF: 10 pages
Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 93010H (24 November 2014); doi: 10.1117/12.2069676
Show Author Affiliations
Feng Xue, National Key Lab. of Science and Technology on Test Physics and Numerical Mathematics (China)
Jiaqi Liu, National Key Lab. of Science and Technology on Test Physics and Numerical Mathematics (China)
Chenyang Mu, National Key Lab. of Science and Technology on Test Physics and Numerical Mathematics (China)
Min Zhao, National Key Lab. of Science and Technology on Test Physics and Numerical Mathematics (China)
Li Zhang, National Key Lab. of Science and Technology on Test Physics and Numerical Mathematics (China)
Shenghai Jiao, National Key Lab. of Science and Technology on Test Physics and Numerical Mathematics (China)


Published in SPIE Proceedings Vol. 9301:
International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition
Gaurav Sharma; Fugen Zhou; Jennifer Liu, Editor(s)

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