Imaging Components, Systems, and Processing

Deblurring for spatial and temporal varying motion with optical computing

[+] Author Affiliations
Xiao Xiao

Xidian University, Department School of Telecommunication Engineering, No. 2 South Taibai Road, Xi’an, Shaanxi 710071, China

Changchun Institute of Applied Chemistry, State Key Laboratory of Rare Earth Resource Utilization, No. 5625, Ren Min Street, Changchun 130012, China

Dongfeng Xue

Changchun Institute of Applied Chemistry, State Key Laboratory of Rare Earth Resource Utilization, No. 5625, Ren Min Street, Changchun 130012, China

Zhao Hui

Xi’an Institute of Optics and Precision Mechanics of CAS, No. 17 Xinxi Road, New Industrial Park, Xi’an 710119, China

Opt. Eng. 55(5), 053103 (May 05, 2016). doi:10.1117/1.OE.55.5.053103
History: Received September 13, 2015; Accepted April 18, 2016
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Abstract.  A way to estimate and remove spatially and temporally varying motion blur is proposed, which is based on an optical computing system. The translation and rotation motion can be independently estimated from the joint transform correlator (JTC) system without iterative optimization. The inspiration comes from the fact that the JTC system is immune to rotation motion in a Cartesian coordinate system. The work scheme of the JTC system is designed to keep switching between the Cartesian coordinate system and polar coordinate system in different time intervals with the ping-pang handover. In the ping interval, the JTC system works in the Cartesian coordinate system to obtain a translation motion vector with optical computing speed. In the pang interval, the JTC system works in the polar coordinate system. The rotation motion is transformed to the translation motion through coordinate transformation. Then the rotation motion vector can also be obtained from JTC instantaneously. To deal with continuous spatially variant motion blur, submotion vectors based on the projective motion path blur model are proposed. The submotion vectors model is more effective and accurate at modeling spatially variant motion blur than conventional methods. The simulation and real experiment results demonstrate its overall effectiveness.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Xiao Xiao ; Dongfeng Xue and Zhao Hui
"Deblurring for spatial and temporal varying motion with optical computing", Opt. Eng. 55(5), 053103 (May 05, 2016). ; http://dx.doi.org/10.1117/1.OE.55.5.053103


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