TY - GEN
T1 - Separating fluorescent and reflective components by using a single hyperspectral image
AU - Zheng, Yinqiang
AU - Fu, Ying
AU - Lam, Antony
AU - Sato, Imari
AU - Sato, Yoichi
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/2/17
Y1 - 2015/2/17
N2 - This paper introduces a novel method to separate fluorescent and reflective components in the spectral domain. In contrast to existing methods, which require to capture two or more images under varying illuminations, we aim to achieve this separation task by using a single hyperspectral image. After identifying the critical hurdle in single-image component separation, we mathematically design the optimal illumination spectrum, which is shown to contain substantial high-frequency components in the frequency domain. This observation, in turn, leads us to recognize a key difference between reflectance and fluorescence in response to the frequency modulation effect of illumination, which fundamentally explains the feasibility of our method. On the practical side, we successfully find an off-the-shelf lamp as the light source, which is strong in irradiance intensity and cheap in cost. A fast linear separation algorithm is developed as well. Experiments using both synthetic data and real images have confirmed the validity of the selected illuminant and the accuracy of our separation algorithm.
AB - This paper introduces a novel method to separate fluorescent and reflective components in the spectral domain. In contrast to existing methods, which require to capture two or more images under varying illuminations, we aim to achieve this separation task by using a single hyperspectral image. After identifying the critical hurdle in single-image component separation, we mathematically design the optimal illumination spectrum, which is shown to contain substantial high-frequency components in the frequency domain. This observation, in turn, leads us to recognize a key difference between reflectance and fluorescence in response to the frequency modulation effect of illumination, which fundamentally explains the feasibility of our method. On the practical side, we successfully find an off-the-shelf lamp as the light source, which is strong in irradiance intensity and cheap in cost. A fast linear separation algorithm is developed as well. Experiments using both synthetic data and real images have confirmed the validity of the selected illuminant and the accuracy of our separation algorithm.
UR - http://www.scopus.com/inward/record.url?scp=84973889506&partnerID=8YFLogxK
U2 - 10.1109/ICCV.2015.402
DO - 10.1109/ICCV.2015.402
M3 - Conference contribution
AN - SCOPUS:84973889506
T3 - Proceedings of the IEEE International Conference on Computer Vision
SP - 3523
EP - 3531
BT - 2015 International Conference on Computer Vision, ICCV 2015
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 15th IEEE International Conference on Computer Vision, ICCV 2015
Y2 - 11 December 2015 through 18 December 2015
ER -