System design of camera for coded exposure

LI Xiang; LI Mingwei; SUN Yi

doi:10.5768/JAO202041.0101001

Journal of Applied Optics > 2020 > 41(1): 1-9. > DOI: 10.5768/JAO202041.0101001

LI Xiang, LI Mingwei, SUN Yi. System design of camera for coded exposure[J]. Journal of Applied Optics, 2020, 41(1): 1-9. DOI: 10.5768/JAO202041.0101001

Citation:

LI Xiang, LI Mingwei, SUN Yi. System design of camera for coded exposure[J]. Journal of Applied Optics, 2020, 41(1): 1-9. DOI: 10.5768/JAO202041.0101001

Citation:

LI Xiang, LI Mingwei, SUN Yi. System design of camera for coded exposure[J]. Journal of Applied Optics, 2020, 41(1): 1-9. DOI: 10.5768/JAO202041.0101001

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System design of camera for coded exposure

LI Xiang^{1, 2,},
LI Mingwei¹,
SUN Yi^1, ,

1.
School of Information and Communication Engineering, Dalian University of Technology, Dalian 116024, China
2.
School of Information Engineering, Dalian Ocean University, Dalian 116023, China

More Information

Received Date: May 27, 2019
Revised Date: September 24, 2019
Available Online: March 30, 2020

Graphical Abstract

Abstract

Abstract

Based on the theory of coded exposure, an applied embedded coded exposure camera system was designed. The exposure shutter of camera was controlled according to the preset coding sequence when collecting the moving target image, and the image of photo-generated charge multiple superimposed with a transfer was obtained. The acquired image was a motion blurred image with coded exposure information, which had more details of the target. The data was temporarily stored in the data memory by the coded exposure image after the AD conversion, and the restored image was decoded by the core device. The experimental results show that the coded exposure camera can effectively solve the problem of linear motion blur. In the same conditions, the index average value of restored image quality under coded exposure condition is increased nearly twice than that of restored image quality under single exposure condition by using the no-reference image evaluation index test.
- coded exposure,
- image deblurring,
- embedded system,
- camera design

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References (19)

References

[1]	鲁晓东. 基于奇异值分解的运动模糊图像广义逆恢复方法[J]. 应用光学,2013,34(1):90-94. LU Xiaodong. Restoration of motion-blurred image by generalizedinverse method based on SVD[J]. Journal of Applied Optics,2013,34(1):90-94.
[2]	SHAN Q, JIA J, AGARWALA A. High-quality motion deblurring from a single image[J]. ACM Transactions on Graphics,2008,27(3):1-10.
[3]	AGRAWAL A, XU Y. Coded exposure deblurring: Optimized codes for PSF estimation and invertibility[C]// 2009 IEEE Conference on Computer Vision and Pattern Recognition. USA: IEEE, 2009: 2066-2073.
[4]	TAI Y W, KONG N, LIN S, et al. Coded exposure imaging for projective motion deblurring[C]//2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.USA: IEEE, 2010, 2408-2415.
[5]	MCCLOSKEY S, VENKATESHA S, MULDOON K, et al. A low-noise fluttering shutter camera handling accelerated motion[C]//2015 IEEE Winter Conference on Applications of Computer Vision.USA: IEEE, 2015: 333-340.
[6]	HUANG K, ZHANG J, HOU J. High-speed video capture by a single flutter shutter camera using three-dimensional hyperbolic wavelets[J]. Optical Review,2014,21(5):509-515. doi: 10.1007/s10043-014-0080-3
[7]	DING Y, MCCLOSKEY S, YU J. Analysis of motion blur with a flutter shutter camera for non-linear motion[J]. European Conference on Computer Vision: Lecture Notes in Computer Science,2010,6311:15-30.
[8]	黄魁华. 信息集成中编码曝光技术优化研究[D]. 国防科学技术大学, 2014. HUANG Kuihua.Optimization of coding exposure technology in information integration[D]. Changsha: National University of Defense Technology, 2014.
[9]	JEON H G, LEE J Y, HAN Y, et al. Generating fluttering patterns with low autocorrelation for coded exposure imaging[J]. International Journal of Computer Vision,2017,123(2):269-286. doi: 10.1007/s11263-016-0976-4
[10]	JEON H G, LEE J Y, HAN Y, et al. Multi-image deblurring using complementary sets of fluttering patterns[J]. IEEE Transactions on Image Processing,2017,26(5):2311-2326. doi: 10.1109/TIP.2017.2675202
[11]	AGRAWAL A, RASKAR R. Optimal single image capture for motion deblurring[C]//2009 IEEE Conference on Computer Vision and Pattern Recognition.USA: IEEE, 2009: 2560-2567.
[12]	HOLLOWAY J, SANKARANARAYANAN A C, VEERARAGHAVAN A, et al. Flutter shutter video camera for compressive sensing of videos[C]//2012 IEEE International Conference on Computational Photography. USA: IEEE, 2012: 1-9.
[13]	HARSHAVARDHAN S, GUPTA S, VENKATESH K S. Flutter shutter based motion deblurring in complex scenes[C]//2013 Annual IEEE India Conference. USA: IEEE, 2013: 1-6.
[14]	ZHANG J, XIONG T, TRAN T, et al. Compact all-CMOS spatiotemporal compressive sensing video camera with pixel-wise coded exposure[J]. Optics Express,2016,24(8):9013-9024. doi: 10.1364/OE.24.009013
[15]	李永远, 谢小平. CCD输出信号处理[J]. 应用光学,1997,18(1):20-23. LI Yongyuan, XIE Xiaoping. CCD output signal processing[J]. Journal of Applied Optics,1997,18(1):20-23.
[16]	LI X, SUN Y. Joint structural similarity and entropy estimation for coded-exposure image restoration[J]. Multimedia Tools and Applications,2018,77(22):29811-29828. doi: 10.1007/s11042-018-5773-3
[17]	HEALEY R K G. CCD camera calibration and noise estimation[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence,1994,16(3):267-276.
[18]	PAN J, HU Z, SU Z, et al. Deblurring text images via L0-regularized intensity and gradient prior[C]//2014 IEEE Conference on Computer Vision and Pattern Recognition. USA: IEEE, 2014: 2901-2908.
[19]	RASKAR R, AGRAWAL A, TUMBLIN J. Coded exposure photography: motion deblurring using fluttered shutter[J]. ACM Transactions on Graphics,2006,25(3):795-804. doi: 10.1145/1141911.1141957

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System design of camera for coded exposure