Robust image restoration for rotary motion blur based on frequency analysis

Yuan F. Zheng; Jianxun Li; Zhengfu Zhu

doi:10.1117/1.2981206

1 September 2008 Robust image restoration for rotary motion blur based on frequency analysis

Yuan F. Zheng, Jianxun Li, Zhengfu Zhu

Author Affiliations +

Optical Engineering, Vol. 47, Issue 9, 097004 (September 2008). https://doi.org/10.1117/1.2981206

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.

©(2008) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Yuan F. Zheng, Jianxun Li, and Zhengfu Zhu "Robust image restoration for rotary motion blur based on frequency analysis," Optical Engineering 47(9), 097004 (1 September 2008). https://doi.org/10.1117/1.2981206

Published: 1 September 2008

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available