[1] Wang G Q. Forensic spectralimaging[J]. Forensic Science and Technology, 7-12(2004).

[2] Gao Q Y, Gao S M. Authentication of age of bloodstains using UV visible reflection spectrum[J]. Spectroscopy and Spectral Analysis, 35, 2221-2224(2015).

[3] Rong N C, Huang M Z. Age estimation of bloodstains based on visible-near infrared multi-spectrum combined ensembling model[J]. Spectroscopy and Spectral Analysis, 40, 168-173(2020).

[4] Li K K. Analysis of blood components by Raman spectroscopy[J]. Spectroscopy and Spectral Analysis, 36, 235-236(2016).

[5] Hou M L, Pan N, Ma Q L et al. Review of hyperspectral imaging technology in analyzing painted artifacts[J]. Spectroscopy and Spectral Analysis, 37, 1852-1860(2017).

[6] Gao Y. Research on dimensionality reduction algorithm for hyperspectral data[D]. Xuzhou: China University of Mining and Technology(2013).

[7] Tang X L, Pearlman W A. Three-dimensional wavelet-based compression of hyperspectral images[M]. Heidelberg: Springer, 273-308(2006).

[8] Wu Q, Zhang R, Xu D W. Hyperspectral data compression based on sparse representation[J]. Journal of Electronics & Information Technology, 37, 78-84(2015).

[9] Chen S X, Zhang Y Q. Hyperspectral image compression based on adaptive band clustering principal component analysis and back propagation neural network[J]. Journal of Electronics & Information Technology, 40, 2478-2483(2018).

[10] Zhao M F, Li C C, Tang B et al. Research on the detection of trace blood based on hyperspectral imaging technology[J]. Laser Journal, 38, 45-49(2017).

[11] Yao Z F, Lei Y, He D J. Identification of powdery mildew and stripe rust in wheat using hyperspectral imaging[J]. Spectroscopy and Spectral Analysis, 39, 969-976(2019).

[12] Xu J, Miao T, Zhou Y C et al. Early detection of curvularia lunata based on hyperspectral imaging[J]. Journal of Shenyang Agricultural University, 51, 225-230(2020).

[13] Xu J P, Zhang B, Lin Y et al. Estimating total suspended sediments concentrations and transparency with hyper-spectral reflectance in Shitoukoumen Reservoir, Jilin Prvoince[J]. Journal of Lake Sciences, 19, 269-274(2007).

[14] Zhao D E, Wu R, Zhao B G et al. Research on garbage classification and recognition based on hyperspectral imaging technology[J]. Spectroscopy and Spectral Analysis, 39, 921-926(2019).

[15] Zhao H T, Feng Y Z, Chen W et al. Application of invasive weed optimization and least square support vector machine for prediction of beef adulteration with spoiled beef based on visible near-infrared (Vis-NIR) hyperspectral imaging[J]. Meat Science, 151, 75-81(2019).

[16] Zhu Y D, He H J, Wang W et al. Quick detection of beef adulteration using hyperspectral imaging technology combined with linear regression algorithm[J]. Science and Technology of Food Industry, 41, 184-189(2020).

[17] Fan X Y, Yang T. Research of forensic application from criminal procedure perspective[J]. Evidence Science, 20, 60-67(2012).

[18] Cantu A A. Advances in the physical, optical, and chemical visualization of latent prints[J]. Proceedings of SPIE, 6741, 67410D(2007).

[19] Barni F, Lewis S W, Berti A et al. Forensic application of the luminol reaction as a presumptive test for latent blood detection[J]. Talanta, 72, 896-913(2007).

[20] Janchaysang S, Sumriddetchkajorn S, Buranasiri P. Tunable filter-based multispectral imaging for detection of blood stains on construction material substrates: part 1: developing blood stain discrimination criteria[J]. Applied Optics, 51, 6984(2012).

[21] Cadd S, Li B, Beveridge P et al. The non-contact detection and identification of blood stained fingerprints using visible wavelength reflectance hyperspectral imaging: Part 1[J]. Science & Justice, 56, 181-190(2016).

[22] Cadd S, Li B, Beveridge P et al. The non-contact detection and identification of blood stained fingerprints using visible wavelength hyperspectral imaging: part II effectiveness on a range of substrates[J]. Science & Justice, 56, 191-200(2016).

[23] Zhu L W, Cai J. Hyperspectral imaging to segment the blood fingerprint image with complicate background[J]. Forensic Science and Technology, 42, 441-445(2017).

[24] Malegori C, Alladio E, Oliveri P et al. Identification of invisible biological traces in forensic evidences by hyperspectral NIR imaging combined with chemometrics[J]. Talanta, 215, 120911(2020).

[25] Chen Z L, Xu Z R, Nie H F et al. Experimental study on absorption laws of the blood components to light[J]. Chinese Journal of Lasers, 21, 77-80(1994).

[26] Yang J, Mathew J J, Dube R R et al. Spectral feature characterization methods for blood stain detection in crime scene backgrounds[J]. Proceedings of SPIE, 9840, 98400E(2016).

[27] Xu S F, Lin S Z, Chen R. Absorption spectrum of blood components in human and rabbit[J]. Proceedings of SPIE, 3344, 212-220(1998).

[28] Kuula J, Puupponen H H, Rinta H et al. The challenges of analysing blood stains with hyperspectral imaging[J]. Proceedings of SPIE, 9112, 91120W(2014).

[29] Huang Q, Li W, Zhang B C et al. Blood cell classification based on hyperspectral imaging with modulated Gabor and CNN[J]. IEEE Journal of Biomedical and Health Informatics, 24, 160-170(2020).

[30] Marotz J, Schulz T, Seider S et al. 3D-perfusion analysis of burn wounds using hyperspectral imaging[J]. Burns, 47, 157-170(2021).

[31] Bremmer R H, Edelman G, Vegter T D et al. Remote spectroscopic identification of bloodstains[J]. Journal of Forensic Sciences, 56, 1471-1475(2011).

[32] Edelman G J, van Leeuwen T G, Aalders M C G. Hyperspectral imaging of the crime scene for detection and identification of blood stains[J]. Proceedings of SPIE, 8743, 87430A(2013).

[33] Li B, Beveridge P, O'Hare W T et al. The application of visible wavelength reflectance hyperspectral imaging for the detection and identification of blood stains[J]. Science & Justice, 54, 432-438(2014).

[34] Lee W C, Khoo B E. Abdullah A F L. A robust background correction algorithm for forensic bloodstain imaging using mean-based contrast adjustment[J]. Science & Justice, 56, 201-209(2016).

[35] Wan X, Wang J, Liu P X et al. Identification of animal whole blood based on near infrared transmission spectroscopy[J]. Spectroscopy and Spectral Analysis, 36, 80-83(2016).

[36] Li C C, Zhao M F, Tang B et al. Application of hyperspectral technology in classification and recognition of bloodstains[J]. Journal of Terahertz Science and Electronic Information Technology, 17, 489-494(2019).

[37] Patterson D. Use of reflectance measurements in assessing the colour changes of ageing bloodstains[J]. Nature, 187, 688-689(1960).

[38] Randeberg L L, Baarstad I, Løke T et al. Hyperspectral imaging of bruised skin[J]. Proceedings of SPIE, 6078, 60780O(2006).

[39] Li B, Beveridge P, O'Hare W T et al. The age estimation of blood stains up to 30 days old using visible wavelength hyperspectral image analysis and linear discriminant analysis[J]. Science & Justice, 53, 270-277(2013).

[40] Edelman G, van Leeuwen T G, Aalders M C G. Hyperspectral imaging for the age estimation of blood stains at the crime scene[J]. Forensic Science International, 223, 72-77(2012).

[41] Bergmann T, Heinke F, Labudde D. Towards substrate-independent age estimation of blood stains based on dimensionality reduction and k-nearest neighbor classification of absorbance spectroscopic data[J]. Forensic Science International, 278, 1-8(2017).

[42] Feng Y, Cai J. Age estimation of the bloodstains on different substrates based on the hyperspectral imaging technology[J]. Laser & Optoelectronics Progress, 57, 053004(2020).