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Optical Engineering

Robust image restoration for rotary motion blur based on frequency analysis
Author(s): Yuan F. Zheng; Jianxun Li; Zhengfu Zhu
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Paper Abstract

Most previous spatial methods to deblur rotary motion blur raise an overregularization problem in the solution of deconvolution. We construct a frequency domain framework to formulate the rotary motion blur. The well-conditioned frequency components are protected so as to avoid the overregularization. Then, Wiener filtering is applied to yield the optimal estimation of original pixels under different noise levels. The identifications of rotary motion parameters are also presented. To detect the rotary center, we develop a zero-interval searching method that works on the degraded pixel spectrum. This method is robust to noise. For the blur angle, it is iteratively calibrated by a novel divide-and-conquer method, which possesses computational efficiency. Furthermore, this paper presents a shape-recognition and linear surface fitting method to interpolate missing pixels caused by circularly fetching. Experimental results illustrate the proposed algorithm outperforms spatial algorithms by up to 0.5–4 dB in the peak signal-to-noise ratio and the improvement of signal-to-noise ratio and prove the methods for missing pixel interpolation and parameter identifications effective.

Paper Details

Date Published: 1 September 2008
PDF: 15 pages
Opt. Eng. 47(9) 097004 doi: 10.1117/1.2981206
Published in: Optical Engineering Volume 47, Issue 9
Show Author Affiliations
Yuan F. Zheng, The Ohio State Univ. (United States)
Jianxun Li, Shanghai Jiao Tong Univ. (China)
Zhengfu Zhu, Shanghai Jiao Tong Univ. (China)

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