1. Li, Q. L., Y. T. Wang, H. Y. Liu, X. F. He, D. R. Xu, J. B. Wang, and F. M. Guo, "Leukocyte cells identification and quantitative morphometry based on molecular hyperspectral imaging technology," Computerized Medical Imaging and Graphics, Vol. 38, No. 3, 171-178, 2014.
doi:10.1016/j.compmedimag.2013.12.008
2. Yao, X., S. Li, and S. L. He, "Dual-mode hyperspectral bio-imager with a conjugated camera for quick object-selection and focusing," Progress In Electromagnetics Research, Vol. 168, 133-143, 2020.
doi:10.2528/PIER20080308
3. Liu, X. M., Z. Q. Jiang, T. C. Wang, F. H. Cai, and D. Wang, "Fast hyperspectral imager driven by a low-cost and compact galvo-mirror," Optik, Vol. 224, 165716, 2020.
doi:10.1016/j.ijleo.2020.165716
4. Wu, D. and D. W. Sun, "Advanced applications of hyperspectral imaging technology for food quality and safety analysis and assessment: A review - Part I: Fundamentals," Innovative Food Sci. Emerg. Technol., Vol. 19, 1-14, 2013.
doi:10.1016/j.ifset.2013.04.014
5. Zdoan, G., X. H. Lin, and D. W. Sun, "Rapid and noninvasive sensory analyses of food products by hyperspectral imaging: Recent application developments," Trends in Food Science & Technology, Vol. 111, 151-165, 2021.
6. Ramakrishnan, D. and R. Bharti, "Hyperspectral remote sensing and geological applications," Current Science, Vol. 108, No. 5, 879-891, 2015.
7. Sun, Y., Y. J. Zhao, K. Qin, J. T. Nie, and H. B. Li, "Geological application of HySpex ground hyperspectral remote sensing in gold and uranium ore deposits," Asia-Pacific Energy Equipment Engineering Research Conference (AP3ER), Vol. 9, 392-395, 2015.
8. Courtenay, L. A., D. Gonzalez-Aguilera, S. Laguela, S. del Pozo, C. Ruiz-Mendez, I. Barbero-Garcia, C. Roman-Curto, J. Canueto, C. Santos-Duran, M. E. Cardenoso-Alvarez, M. Roncero-Riesco, D. Hernandez-Lopez, D. Guerrero-Sevilla, and P. Rodriguez-Gonzalvez, "Hyperspectral imaging and robust statistics in non-melanoma skin cancer analysis," Biomed. Opt. Express, Vol. 12, No. 8, 5107-5127, 2021.
doi:10.1364/BOE.428143
9. Dicker, D. T., J. Lerner, P. Van Belle, S. F. Barth, D. Guerry, M. Herlyn, and W. S. El-Deiry, "Differentiation of normal skin and melanoma using high resolution hyperspectral imaging," Cancer Biology & Therapy, Vol. 5, No. 8, 1033-1038, 2006.
doi:10.4161/cbt.5.8.3261
10. Manley, M., "Near-infrared spectroscopy and hyperspectral imaging: Non-destructive analysis of biological materials," Chem. Soc. Rev., Vol. 43, No. 24, 8200-8214, 2014.
doi:10.1039/C4CS00062E
11. Studer, V., J. Bobin, M. Chahid, H. S. Mousavi, E. Candes, and M. Dahan, "Compressive fluorescence microscopy for biological and hyperspectral imaging," Proceedings of the National Academy of Sciences of the United States of America, Vol. 109, No. 26, E1679-E1687, 2012.
12. Yang, Q. L., B. Niu, S. Q. Gu, J. G. Ma, C. M. Zhao, Q. Chen, D. H. Guo, X. J. Deng, Y. A. Yu, and F. Zhang, "Rapid detection of nonprotein nitrogen adulterants in milk powder using point-scan raman hyperspectral imaging technology," ACS Omega, Vol. 7, No. 2, 2064-2073, 2022.
doi:10.1021/acsomega.1c05533
13. Yao, X. L., F. H. Cai, P. Y. Zhu, H. X. Fang, J. W. Li, and S. L. He, "Non-invasive and rapid pH monitoring for meat quality assessment using a low-cost portable hyperspectral scanner," Meat Sci., Vol. 152, 73-80, 2019.
doi:10.1016/j.meatsci.2019.02.017
14. Gomez-Sanchis, J., J. Blasco, E. Soria-Olivas, D. Lorente, P. Escandell-Montero, J. M. Martinez-Martinez, M. Martinez-Sober, and N. Aleixos, "Hyperspectral LCTF-based system for classification of decay in mandarins caused by Penicilliumdigitatum and Penicilliumitalicum using the most relevant bands and non-linear classifiers," Postharvest Biol. Technol., Vol. 82, 76-86, 2013.
doi:10.1016/j.postharvbio.2013.02.011
15. Abdlaty, R., J. Orepoulos, P. Sinclair, R. Berman, and Q. Y. Fang, "High throughput AOTF hyperspectral imager for randomly polarized light," Photonics, Vol. 5, No. 1, 3, 2018.
doi:10.3390/photonics5010003
16. Gat, N., "Imaging spectroscopy using tunable filters: A review," Conference on Wavelet Applications VII, Vol. 4056, 50-64, 2000.
doi:10.1117/12.381686
17. Wang, X., Y. Zhang, X. Ma, T. Xu, and G. R. Arce, "Compressive spectral imaging system based on liquid crystal tunable filter," Opt. Express, Vol. 26, No. 19, 25226-25243, 2018.
doi:10.1364/OE.26.025226
18. Gebhart, S. C., R. C. Thompson, and A. Mahadevan-Jansen, "Liquid-crystal tunable filter spectral imaging for brain tumor demarcation," Appl. Opt., Vol. 46, No. 10, 1896-1910, 2007.
doi:10.1364/AO.46.001896
19. Nalpantidis, L., G. C. Sirakoulis, and A. Gasteratos, "Review of stereo vision algorithms: From software to hardware," Int. J. Optomechatronics, Vol. 2, No. 4, 435-462, 2008.
doi:10.1080/15599610802438680
20. Dhond, U. R. and J. K. Aggarwal, "Structure from stereo - A review," IEEE Transactions on Systems Man and Cybernetics, Vol. 19, No. 6, 1489-1510, 1989.
doi:10.1109/21.44067
21. Zhang, S., "High-speed 3D shape measurement with structured light methods: A review," Opt. Lasers Eng., Vol. 106, 119-131, 2018.
doi:10.1016/j.optlaseng.2018.02.017
22. Hyun, J. S., G. T. C. Chiu, and S. Zhang, "High-speed and high-accuracy 3D surface measurement using a mechanical projector," Opt. Express, Vol. 26, No. 2, 1474-1487, 2018.
doi:10.1364/OE.26.001474
23. Foix, S., G. Alenya, and C. Torras, "Lock-in Time-of-Flight (ToF) cameras: A survey," IEEE Sens. J., Vol. 11, No. 9, 1917-1926, 2011.
doi:10.1109/JSEN.2010.2101060
24. Luo, L. Q., X. Chen, Z. P. Xu, S. Li, Y. R. Sun, and S. L. He, "A parameter-free calibration process for a scheimpflug LIDAR for volumetric profiling," Progress In Electromagnetics Research, Vol. 169, 117-127, 2020.
doi:10.2528/PIER20120701
25. Zhong, K., Z. W. Li, X. H. Zhou, Y. F. Li, Y. S. Shi, and C. J. Wang, "Enhanced phase measurement profilometry for industrial 3D inspection automation," Int. J. Adv. Manuf. Technol., Vol. 76, No. 9-12, 1563-1574, 2015.
doi:10.1007/s00170-014-6360-z
26. Caudullo, P. T., "3D laser scanning: Technology at the service of the protection of cultural heritage," Archeomatica-Tecnologie Per I Beni Culturali, Vol. 11, No. 3, 6-9, 2020.
27. Jahanshahi, M. R. and S. F. Masri, "Adaptive vision-based crack detection using 3D scene reconstruction for condition assessment of structures," Autom. Constr., Vol. 22, 567-576, 2012.
doi:10.1016/j.autcon.2011.11.018
28. Peng, H. C., Z. C. Ruan, F. H. Long, J. H. Simpson, and E. W. Myers, "V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets," Nat. Biotechnol., Vol. 28, No. 4, 348-375, 2010.
doi:10.1038/nbt.1612
29. Cai, F. H., T. C. Wang, J. J. Wu, and X. Y. Zhang, "Handheld four-dimensional optical sensor," Optik, Vol. 203, 164001, 2020.
doi:10.1016/j.ijleo.2019.164001
30. Aasen, H., A. Burkart, A. Bolten, and G. Bareth, "Generating 3D hyperspectral information with lightweight UAV snapshot cameras for vegetation monitoring: From camera calibration to quality assurance," ISPRS J. Photogramm. Remote Sens., Vol. 108, 245-259, 2015.
doi:10.1016/j.isprsjprs.2015.08.002
31. Zhao, H. J., Z. Y. Wang, G. R. Jia, X. D. Li, and Y. Zhang, "Field imaging system for hyperspectral data, 3D structural data and panchromatic image data measurement based on acousto-optic tunable filter," Opt. Express, Vol. 26, No. 13, 17717-17730, 2018.
doi:10.1364/OE.26.017717
32. Zhao, H. J., L. B. Xu, S. G. Shi, H. Z. Jiang, and D. Chen, "A high throughput integrated hyperspectral imaging and 3D measurement system," Sensors, Vol. 18, No. 4, 1608, 2018.
33. Heist, S., C. Zhang, K. Reichwald, P. Kuhmstedt, G. Notni, and A. Tuennermann, "5D hyperspectral imaging: Fast and accurate measurement of surface shape and spectral characteristics using structured light," Opt. Express, Vol. 26, No. 18, 23366-23379, 2018.
doi:10.1364/OE.26.023366
34. Luo, J., S. Li, E. Forsberg, and S. L. He, "4D surface shape measurement system with high spectral resolution and great depth accuracy," Opt. Express, Vol. 29, No. 9, 13048-13070, 2021.
doi:10.1364/OE.423755
35. Ivorra, E., S. Verdu, A. J. Sanchez, R. Grau, and J. M. Barat, "Predicting gilthead sea bream (Sparus aurata) freshness by a novel combined technique of 3D imaging and SW-NIR spectral analysis," Sensors, Vol. 16, No. 10, 1735, 2016.
doi:10.3390/s16101735
36. Kim, M. H., H. Rushmeier, J. Dorsey, T. A. Harvey, R. O. Prum, D. S. Kittle, and D. J. Brady, "3D imaging spectroscopy for measuring hyperspectral patterns on solid objects," ACM Trans. Graphics, Vol. 31, No. 4, 1-11, 2012.
doi:10.1145/3450626.3459776
37. Chen, B. W., S. Shi, J. Sun, W. Gong, J. Yang, L. Du, K. H. Guo, B. H. Wang, and B. W. Chen, "Hyperspectral lidar point cloud segmentation based on geometric and spectral information," Opt. Express, Vol. 27, No. 17, 24043-24059, 2019.
doi:10.1364/OE.27.024043
38. Li, J. Q., Y. Zheng, L. L. Liu, and B. W. Li, "4D line-scan hyperspectral imaging," Opt. Express, Vol. 29, No. 21, 34835-34849, 2021.
doi:10.1364/OE.441213
39. Beeckman, J., K. Neyts, and P. J. M. Vanbrabant, "Liquid-crystal photonic applications," Opt. Eng., Vol. 50, No. 8, 081202, 2011.
doi:10.1117/1.3565046
40. Aharon, O. and I. Abdulhalim, "Tunable optical filter having a large dynamic range," Opt. Lett., Vol. 34, No. 14, 2114-2116, 2009.
doi:10.1364/OL.34.002114
41. Zuo, C., S. J. Feng, L. Huang, T. Y. Tao, W. Yin, and Q. Chen, "Phase shifting algorithms for fringe projection profilometry: A review," Opt. Lasers Eng., Vol. 109, 23-59, 2018.
doi:10.1016/j.optlaseng.2018.04.019
42. Reich, C., R. Ritter, and J. Thesing, "White light heterodyne principle for 3D-measurement," Proc. SPIE, Vol. 3100, No. 1, 236-244, 1997.
doi:10.1117/12.287750
43. Li, Z., Y. Shi, C. Wang, and Y. Wang, "Accurate calibration method for a structured light system," Opt. Eng., Vol. 47, No. 5, 053604, 2008.
doi:10.1117/1.2931517
44. Bajguz, A. and A. Tretyn, "The chemical characteristic and distribution of brassinosteroids in plants," Phytochemistry, Vol. 62, No. 7, 1027-1046, 2003.
doi:10.1016/S0031-9422(02)00656-8
45. Pilsl, U., F. Anderhuber, and S. Neugebauer, "The facial artery-the main blood vessel for the anterior face?," Dermatologic Surgery, Vol. 42, No. 2, 203-208, 2016.
doi:10.1097/DSS.0000000000000599