Single-pixel imaging experiment through 34 km horizontal atmosphere

Li Mingfei; Kan Baoxi; Huo Juan; Yan Lu; Liu Yuanxing

doi:10.3788/IRLA201948.0925002

Experimental setup of long distance and high resolution single-pixel imaging system was set up. Images of natural target were obtained through 34 km outdoors horizontal atmosphere in daylight, about 0.8 m resolution was achieved. The multiple resolution level of Hadamard matrix was used as measurement basis, and owing to 25% compressive sampling and differential measuring by two photon-multiplier tubes, video frame rate of 2 Hz@128128 pixels was achieved with the proposed hardware and fast Walsh transform algorithm. An signal-to-noise ratio(SNR) was defined based on human-computer interaction interface to estimate the qualities of the recovered images. The relationship between image qualities and exposure times were researched. The proposed scheme has the potential application in long distance and high resolution infrared imaging with low cost setup.

Single-pixel imaging experiment through 34 km horizontal atmosphere

1. Beijing Institute of Aerospace Control Devices,Beijing 100039,China;

2. Quantum Engineering Research Center,China Aerospace Science and Technology Corporation,Beijing 100094,China

Received Date: 2019-04-05

Rev Recd Date: 2019-05-03

Publish Date: 2019-09-25

Key words:

Abstract: Experimental setup of long distance and high resolution single-pixel imaging system was set up. Images of natural target were obtained through 34 km outdoors horizontal atmosphere in daylight, about 0.8 m resolution was achieved. The multiple resolution level of Hadamard matrix was used as measurement basis, and owing to 25% compressive sampling and differential measuring by two photon-multiplier tubes, video frame rate of 2 Hz@128128 pixels was achieved with the proposed hardware and fast Walsh transform algorithm. An signal-to-noise ratio(SNR) was defined based on human-computer interaction interface to estimate the qualities of the recovered images. The relationship between image qualities and exposure times were researched. The proposed scheme has the potential application in long distance and high resolution infrared imaging with low cost setup.

HTML

Reference (18)

[1]	Donoho D. Compressed sensing[J]. IEEE Trans Inf Theory, 2006, 52(4):1289.
[2]	Cand'es E J, Romberg J, Tao T. Robust uncertainty principles:exact signal reconstruction from highly incomplete frequency information[J]. IEEE Trans Inf Theory, 2006, 52(2):489.
[3]	Duarte M, Davenport M, Takhar D, et al. Single-pixel imaging via compressive sampling[J]. IEEE Signal Process Mag, 2008, 25(2):83.
[4]	Yu Wenkai, Yao Xuri, Liu Xuefeng, et al. Compressed sensing for ultra-weak light counting imaging[J]. Opt Precision Eng, 2012, 20(10):2283-2292. (in Chinese)
[5]	Olivas S, Rachlin Y, Gu L, et al. Characterization of a compressive imaging system using laboratory and natural light scenes[J]. Appl Opt, 2013, 52:4515-4526.
[6]	Ma Jingting, Liu Zunlong, Wang Minhang, et al. Modulated multi-wavelength correlated imaging system with DMD[J]. Infrared and Laser Engineering, 2017, 46(9):0924001. (in Chinese)
[7]	Ori K, Yaron B, Yaron S. Compressive ghost imaging[J]. Appl Phys Lett, 2009, 95(13):131110.
[8]	Sun B, Edgar M P, Bowman R, et al. 3D computational imaging with single-pixel detectors[J]. Science, 2013, 340:844-847.
[9]	Li Mingfei, Mo Xiaofan, Zhang An'ning. The key technics in quantum imaging and its researching status[J]. Navigation and Control, 2015, 5(15):1. (in Chinese)
[10]	Beauchamp K G. Applications of walsh and related functions, with an introduction to sequency theory[M]. New York:Academic Press, 1984.
[11]	An Xiaofeng, Li Yanqiu, Ma Haiyu, et al. Research on thresholding method of Hadamard coded modulation correlation imaging[J]. Infrared and Laser Engineering, 2018, 47(10):1041002. (in Chinese)
[12]	Bhagavan B K, Polge R J. Sequencing the Hadamard transform[J]. IEEE Transactions on Audio and Electroacoustics, 1973, 21(5):472-473.
[13]	Li Mingfei, Mo Xiaofan, Zhao Lianjie, et al. Single-pixel remote imaging based on Walsh-Hadamard transform[J]. Acta Phys Sin, 2016, 65(6):064201. (in Chinese)
[14]	Sun Mingjie, Meng Litong, Edgar M P, et al. A Russian Dolls ordering of the Hadamard basis for compressive single-pixel imaging[J]. Scientific Reports, 2017, 7(1):3464.
[15]	Rafael C Gonzlez, Richard E W. Digital image processing[J]. Prentice Hall, 2008, 354:ISBN0-13-168728-X.
[16]	Huo Juan, Li Mingfei, Yang Ran, et al. High sensitive near infrared imaging system based on single element detectors[J]. Infrared and Laser Engineering, 2016, 45(S1):S104001. (in Chinese)
[17]	Howland G A, Lum D J, Ware M R, et al. Photon counting compressive depth mapping[J]. Opt Express, 2013, 21(20):23822.
[18]	Gong Wenlin, Wang Chenglong, Mei Xiaodong, et al. Recent research progress and thoughts on GISC lidar with respect to practical applications[J]. Infrared and Laser Engineering, 2018, 47(7):0702001. (in Chinese)

Single-pixel imaging experiment through 34 km horizontal atmosphere

doi: 10.3788/IRLA201948.0925002

Abstract

References

Proportional views

通讯作者: 陈斌, bchen63@163.com

Article Metrics

Related

Proportional views