Multispectral imaging using a single bucket detector

Liheng Bian; Jinli Suo; Guohai Situ; Ziwei Li; Jingtao Fan; Feng Chen; Qionghai Dai

doi:10.1038/srep24752

journal article Open Access Apr 22, 2016

Multispectral imaging using a single bucket detector

Liheng Bian

Scientific Reports Vol. 6 No. 1 · Springer Science and Business Media LLC

View at Publisher Save 10.1038/srep24752

Abstract

AbstractExisting multispectral imagers mostly use available array sensors to separately measure 2D data slices in a 3D spatial-spectral data cube. Thus they suffer from low photon efficiency, limited spectrum range and high cost. To address these issues, we propose to conduct multispectral imaging using a single bucket detector, to take full advantage of its high sensitivity, wide spectrum range, low cost, small size and light weight. Technically, utilizing the detector’s fast response, a scene’s 3D spatial-spectral information is multiplexed into a dense 1D measurement sequence and then demultiplexed computationally under the single pixel imaging scheme. A proof-of-concept setup is built to capture multispectral data of 64 pixels × 64 pixels × 10 wavelength bands ranging from 450 nm to 650 nm, with the acquisition time being 1 minute. The imaging scheme holds great potentials for various low light and airborne applications and can be easily manufactured as production-volume portable multispectral imagers.

Topics

No keywords indexed for this article. Browse by subject →

References

38

[1]

Spectral imaging: Principles and applications

Yuval Garini, Ian T. Young, George McNamara

Cytometry Part A 2006 10.1002/cyto.a.20311

[2]

Gat, N. Imaging spectroscopy using tunable filters: a review. In AeroSense 2000, 50–64 (SPIE, 2000). 10.1117/12.381686

[3]

James, J. Spectrograph design fundamentals (Cambridge University Press, 2007). 10.1017/cbo9780511534799

[4]

Bao, J. & Bawendi, M. G. A colloidal quantum dot spectrometer. Nature 523, 67–70 (2015). 10.1038/nature14576

[5]

Compressive Coded Aperture Spectral Imaging: An Introduction

Gonzalo R. Arce, David J. Brady, Lawrence Carin et al.

IEEE Signal Processing Magazine 2014 10.1109/msp.2013.2278763

[6]

Garini, Y. et al. Spectral karyotyping. Bioimaging 4, 65–72 (1996). 10.1002/1361-6374(199606)4:2<65::aid-bio4>3.3.co;2-4

[7]

Coffey, V. C. Hyperspectral imaging for safety and security. Opt. Photonics News 26, 26–33 (2015). 10.1364/opn.26.10.000026

[8]

Duarte, M. F. et al. Single-pixel imaging via compressive sampling. IEEE Signal Proc. Mag. 25, 83 (2008). 10.1109/msp.2007.914730

[9]

Shapiro, J. H. Computational ghost imaging. Phys. Rev. A 78, 061802 (2008). 10.1103/physreva.78.061802

[10]

Edgar, M. P. et al. Simultaneous real-time visible and infrared video with single-pixel detectors. Sci. Rep. 5, 10669 (2015). 10.1038/srep10669

[11]

Schechner, Y. Y., Nayar, S. K. & Belhumeur, P. N. Multiplexing for optimal lighting. IEEE T. Pattern Anal. 29, 1339–1354 (2007). 10.1109/tpami.2007.1151

[12]

Davis, B. M. et al. Multivariate hyperspectral raman imaging using compressive detection. Anal. Chem. 83, 5086–5092 (2011). 10.1021/ac103259v

[13]

Imaging with a small number of photons

Peter A. Morris, Reuben S. Aspden, Jessica E. C. Bell et al.

Nature Communications 2015 10.1038/ncomms6913

[14]

Single-pixel imaging by means of Fourier spectrum acquisition

Zhouyang Zhang, Xiao Ma, Jingang Zhong

Nature Communications 2015 10.1038/ncomms7225

[15]

Sun, B. et al. 3D computational imaging with single-pixel detectors. Science 340, 844–847 (2013). 10.1126/science.1234454

[16]

Tian, N., Guo, Q., Wang, A., Xu, D. & Fu, L. Fluorescence ghost imaging with pseudothermal light. Opt. Lett. 36, 3302–3304 (2011). 10.1364/ol.36.003302

[17]

Clemente, P., Durán, V., Tajahuerce, E., Lancis, J. et al. Optical encryption based on computational ghost imaging. Opt. Lett. 35, 2391–2393 (2010). 10.1364/ol.35.002391

[18]

Zhao, C. et al. Ghost imaging lidar via sparsity constraints. Appl. Phys. Lett. 101, 141123 (2012). 10.1063/1.4757874

[19]

Cheng, J. Ghost imaging through turbulent atmosphere. Opt. Express 17, 7916–7921 (2009). 10.1364/oe.17.007916

[20]

Magaña-Loaiza, O. S., Howland, G. A., Malik, M., Howell, J. C. & Boyd, R. W. Compressive object tracking using entangled photons. Appl. Phys. Lett. 102, 231104 (2013). 10.1063/1.4809836

[21]

Li, C., Sun, T., Kelly, K. F. & Zhang, Y. A compressive sensing and unmixing scheme for hyperspectral data processing. IEEE T. on Image Process. 21, 1200–1210 (2012). 10.1109/tip.2012.2201489

[22]

MagalhÃŖes, F., Abolbashari, M., AraÃējo, F. M., Correia, M. V. & Farahi, F. High-resolution hyperspectral single-pixel imaging system based on compressive sensing. Opt. Eng. 51, 071406–1 (2012). 10.1117/1.oe.51.7.071406

[23]

Welsh, S. S. et al. Fast full-color computational imaging with single-pixel detectors. Opt. Express 21, 23068–23074 (2013). 10.1364/oe.21.023068

[24]

Single-pixel infrared and visible microscope

Neal Radwell, Kevin J. Mitchell, Graham M. Gibson et al.

Optica 2014 10.1364/optica.1.000285

[25]

August, Y., Vachman, C., Rivenson, Y. & Stern, A. Compressive hyperspectral imaging by random separable projections in both the spatial and the spectral domains. Appl. Opt. 52, D46–D54 (2013). 10.1364/ao.52.000d46

[26]

Suo, J. et al. A self-synchronized high speed computational ghost imaging system: A leap towards dynamic capturing. Opt. Laser Technol. 74, 65–71 (2015). 10.1016/j.optlastec.2015.05.007

[27]

Schechner, Y. Y., Nayar, S. K. & Belhumeur, P. N. A theory of multiplexed illumination. In IEEE Int. Conf. Comput. Vision, vol. 2, 808–815 (2003). 10.1109/iccv.2003.1238431

[28]

Studer, V. et al. Compressive fluorescence microscopy for biological and hyperspectral imaging. P. Natl. Acad. Sci. 109, E1679–E1687 (2012). 10.1073/pnas.1119511109

[29]

Shaw, G. A. & Burke, H.-h. K. Spectral imaging for remote sensing. Lincoln Laboratory Journal 14, 3–28 (2003).

[30]

Mohan, A., Raskar, R. & Tumblin, J. Agile spectrum imaging: Programmable wavelength modulation for cameras and projectors. In Comput. Graph. Forum, vol. 27, 709–717 (2008). 10.1111/j.1467-8659.2008.01169.x

[31]

Lin, Z., Liu, R. & Su, Z. Linearized alternating direction method with adaptive penalty for low-rank representation. In Adv. Neural Inform. Proc. Sys., 612–620 (Curran Associates, Inc., 2011).

[32]

Jiang, J., Liu, D., Gu, J. & Susstrunk, S. What is the space of spectral sensitivity functions for digital color cameras? In IEEE Appl. Comput. Vision, 168–179 (IEEE, 2013). 10.1109/wacv.2013.6475015

[33]

Bian, L., Suo, J., Hu, X., Chen, F. & Dai, Q. Fourier computational ghost imaging using spectral sparsity and conjugation priors. arXiv preprint arXiv:1504.03823 (2015).

[34]

Heide, F. et al. High-quality computational imaging through simple lenses. ACM T. Graphic. 32, 149 (2013).

[35]

Han, S., Sato, I., Okabe, T. & Sato, Y. Fast spectral reflectance recovery using dlp projector. Int. J. Comput. Vision 110, 172–184 (2014). 10.1007/s11263-013-0687-z

[36]

Suo, J., Bian, L., Chen, F. & Dai, Q. Signal-dependent noise removal for color videos using temporal and cross-channel priors. J. Vis. Commun. Image R. 36, 130–141 (2016). 10.1016/j.jvcir.2016.01.009

[37]

Bloomfield, P. Fourier analysis of time series: an introduction (John Wiley & Sons, 2004).

[38]

Marcellin, M. W. JPEG2000 Image Compression Fundamentals, Standards and Practice: Image Compression Fundamentals, Standards and Practice, vol. 1 (Springer Science & Business Media, 2002).

Cited By

181

A compressive hyperspectral video imaging system using a single-pixel detector

Yibo Xu, Liyang Lu · 2024

Nature Communications

Comparison of Common Algorithms for Single-Pixel Imaging via Compressed Sensing

Wenjing Zhao, Lei Gao · 2023

Sensors

Metrics

181

Citations

38

References

Details

Published: Apr 22, 2016
Vol/Issue: 6(1)
License: View

Authors

L

Liheng Bian

MIIT Key Laboratory of Complex-Field Intelligent Sensing, Beijing Institute of Technology, Beijing, China

Changchun University of Science and Technology

Q

Qionghai Dai

Cite This Article

Liheng Bian, Jinli Suo, Guohai Situ, et al. (2016). Multispectral imaging using a single bucket detector. Scientific Reports, 6(1). https://doi.org/10.1038/srep24752

Multispectral imaging using a single bucket detector

You May Also Like