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Proceedings Paper

Robust grid registration for non-blind PSF estimation
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Paper Abstract

Given a blurred image of a known test grid and an accurate estimate of the unblurred image, it has been demonstrated that the underlying blur kernel (or point-spread function, PSF) can be reliably estimated. Unfortunately, the estimate of the sharp image can be sensitive to common imperfections in the setup used to obtain the blurred image, and errors in the image estimate result in an unreliable PSF estimate. We propose a robust ad-hoc method to estimate a sharp prior image, given a blurry, noisy image of the test grid from Joshi1 taken in imperfect lab and lighting conditions. The proposed algorithm is able to reliably reject superfluous image content, can deal with spatially-varying lighting, and is insensitive to errors in alignment of the grid with the image plane. We demonstrate the algorithms performance through simulation, and with a set of test images. We also show that our grid registration algorithm leads to improved PSF estimation and deblurring, compared to an affine registration using spatially invariant lighting correction.

Paper Details

Date Published: 15 February 2012
PDF: 8 pages
Proc. SPIE 8305, Visual Information Processing and Communication III, 83050I (15 February 2012); doi: 10.1117/12.909887
Show Author Affiliations
Jonathan D. Simpkins, Univ. of Notre Dame (United States)
Robert L. Stevenson, Univ. of Notre Dame (United States)


Published in SPIE Proceedings Vol. 8305:
Visual Information Processing and Communication III
Amir Said; Onur G. Guleryuz; Robert L. Stevenson, Editor(s)

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