TY - JOUR
T1 - Measuring spatially varying, multispectral, ultraviolet bidirectional reflectance distribution function with an imaging spectrometer
AU - Li, Hongsong
AU - Lyu, Hang
AU - Liao, Ningfang
AU - Wu, Wenmin
N1 - Publisher Copyright:
© 2016 The Authors.
PY - 2016/12/1
Y1 - 2016/12/1
N2 - The bidirectional reflectance distribution function (BRDF) data in the ultraviolet (UV) band are valuable for many applications including cultural heritage, material analysis, surface characterization, and trace detection. We present a BRDF measurement instrument working in the near-and middle-UV spectral range. The instrument includes a collimated UV light source, a rotation stage, a UV imaging spectrometer, and a control computer. The data captured by the proposed instrument describe spatial, spectral, and angular variations of the light scattering from a sample surface. Such a multidimensional dataset of an example sample is captured by the proposed instrument and analyzed by a k-mean clustering algorithm to separate surface regions with same material but different surface roughnesses. The clustering results show that the angular dimension of the dataset can be exploited for surface roughness characterization. The two clustered BRDFs are fitted to a theoretical BRDF model. The fitting results show good agreement between the measurement data and the theoretical model.
AB - The bidirectional reflectance distribution function (BRDF) data in the ultraviolet (UV) band are valuable for many applications including cultural heritage, material analysis, surface characterization, and trace detection. We present a BRDF measurement instrument working in the near-and middle-UV spectral range. The instrument includes a collimated UV light source, a rotation stage, a UV imaging spectrometer, and a control computer. The data captured by the proposed instrument describe spatial, spectral, and angular variations of the light scattering from a sample surface. Such a multidimensional dataset of an example sample is captured by the proposed instrument and analyzed by a k-mean clustering algorithm to separate surface regions with same material but different surface roughnesses. The clustering results show that the angular dimension of the dataset can be exploited for surface roughness characterization. The two clustered BRDFs are fitted to a theoretical BRDF model. The fitting results show good agreement between the measurement data and the theoretical model.
KW - bidirectional reflectance distribution function
KW - hyperspectral imaging
KW - scattering measurement
KW - ultraviolet spectroscopy
UR - http://www.scopus.com/inward/record.url?scp=85007518194&partnerID=8YFLogxK
U2 - 10.1117/1.OE.55.12.124106
DO - 10.1117/1.OE.55.12.124106
M3 - Article
AN - SCOPUS:85007518194
SN - 0091-3286
VL - 55
JO - Optical Engineering
JF - Optical Engineering
IS - 12
M1 - 124106
ER -