Reflective and Fluorescent Separation Under Narrow-Band Illumination

Koji Koyamatsu, Daichi Hidaka, Takahiro Okabe, Hendrik P. A. Lensch; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019, pp. 7577-7585

In this paper, we address the separation of reflective and fluorescent components in RGB images taken under narrow-band light sources such as LEDs. First, we show that the fluorescent color per pixel can be estimated from at least two images under different light source colors, because the observed color at a surface point is represented by a convex combination of the light source color and the illumination-invariant fluorescent color. Second, we propose a method for robustly estimating the fluorescent color via MAP estimation by taking the prior knowledge with respect to fluorescent colors into consideration. We conducted a number of experiments by using both synthetic and real images, and confirmed that our proposed method works better than the closely related state-of-the-art method and enables us to separate reflective and fluorescent components even from a single image. Furthermore, we demonstrate that our method is effective for applications such as image-based material editing and relighting.