Saturation-Preserving Specular Reflection Separation

Yuanliu Liu, Zejian Yuan, Nanning Zheng, Yang Wu; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015, pp. 3725-3733

Abstract


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.

Related Material


[pdf]
[bibtex]
@InProceedings{Liu_2015_CVPR,
author = {Liu, Yuanliu and Yuan, Zejian and Zheng, Nanning and Wu, Yang},
title = {Saturation-Preserving Specular Reflection Separation},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2015}
}