Imaging Components, Systems, and Processing

Fast approach to infrared image restoration based on shrinkage functions calibration

[+] Author Affiliations
Chengshuo Zhang

Chinese Academy of Sciences, Shenyang Institute of Automation, No. 114 Nanta Street, Shenyang 110016, China

Chinese Academy of Sciences, Key Laboratory of Optical-Electronics Information Processing, No. 114 Nanta Street, Shenyang 110016, China

University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China

Zelin Shi, Baoshu Xu, Bin Feng

Chinese Academy of Sciences, Shenyang Institute of Automation, No. 114 Nanta Street, Shenyang 110016, China

University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China

Opt. Eng. 55(5), 053107 (May 20, 2016). doi:10.1117/1.OE.55.5.053107
History: Received December 2, 2015; Accepted April 22, 2016
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Abstract.  High-quality image restoration in real time is a challenge for infrared imaging systems. We present a fast approach to infrared image restoration based on shrinkage functions calibration. Rather than directly modeling the prior of sharp images to obtain the shrinkage functions, we calibrate them for restoration directly by using the acquirable sharp and blurred image pairs from the same infrared imaging system. The calibration method is employed to minimize the sum of squared errors between sharp images and restored images from the blurred images. Our restoration algorithm is noniterative and its shrinkage functions are stored in the look-up tables, so an architecture solution of pipeline structure can work in real time. We demonstrate the effectiveness of our approach by testing its quantitative performance from simulation experiments and its qualitative performance from a developed wavefront coding infrared imaging system.

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© 2016 Society of Photo-Optical Instrumentation Engineers

Citation

Chengshuo Zhang ; Zelin Shi ; Baoshu Xu and Bin Feng
"Fast approach to infrared image restoration based on shrinkage functions calibration", Opt. Eng. 55(5), 053107 (May 20, 2016). ; http://dx.doi.org/10.1117/1.OE.55.5.053107


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