TY - GEN
T1 - Saturation-preserving specular reflection separation
AU - Liu, Yuanliu
AU - Yuan, Zejian
AU - Zheng, Nanning
AU - Wu, Yang
N1 - Publisher Copyright:
© 2015 IEEE.
PY - 2015/10/14
Y1 - 2015/10/14
N2 - Specular reflection generally decreases the saturation of surface colors, which will be possibly confused with other colors that have the same hue but lower saturation. Traditional methods for specular reflection separation suffer this problem of hue-saturation ambiguity, producing over-saturated specular-free images quite often. We proposed a two-step approach to solve this problem. In the first step, we produce an over-saturated specular-free image by global chromaticity propagation from specular-free pixels to highlighted ones. Then we recover the saturation based on priors of the piecewise constancy of diffuse chromaticity as well as the spatial sparsity and smoothness of specular reflection. We achieve this through increasing the achromatic component of diffuse chromaticity, while the magnitudes of increments are determined by linear programming under the constraints derived from the priors. Experiments on both laboratory and natural images show that our method can separate the specular reflection while preserving the saturation of the underlying surface colors.
AB - Specular reflection generally decreases the saturation of surface colors, which will be possibly confused with other colors that have the same hue but lower saturation. Traditional methods for specular reflection separation suffer this problem of hue-saturation ambiguity, producing over-saturated specular-free images quite often. We proposed a two-step approach to solve this problem. In the first step, we produce an over-saturated specular-free image by global chromaticity propagation from specular-free pixels to highlighted ones. Then we recover the saturation based on priors of the piecewise constancy of diffuse chromaticity as well as the spatial sparsity and smoothness of specular reflection. We achieve this through increasing the achromatic component of diffuse chromaticity, while the magnitudes of increments are determined by linear programming under the constraints derived from the priors. Experiments on both laboratory and natural images show that our method can separate the specular reflection while preserving the saturation of the underlying surface colors.
UR - https://www.scopus.com/pages/publications/84959234638
U2 - 10.1109/CVPR.2015.7298996
DO - 10.1109/CVPR.2015.7298996
M3 - 会议稿件
AN - SCOPUS:84959234638
T3 - Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
SP - 3725
EP - 3733
BT - IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
PB - IEEE Computer Society
T2 - IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2015
Y2 - 7 June 2015 through 12 June 2015
ER -