Camera Spectral Sensitivity Estimation from a Single Image under Unknown Illumination by using Fluorescence

By | January 1, 2012

Shuai Han, Yasuyuki Matsushita, Imari Sato, Takahiro Okabe, and Yoichi Sato: “Camera Spectral Sensitivity Estimation from a Single Image under Unknown Illumination by using Fluorescence”. In Proc. IEEE Conference on Computer Vision and Pattern Recognition (CVPR2012), pp. 805-812, June 2012.

Camera spectral sensitivity plays an important role for various color-based computer vision tasks. Although several methods have been proposed to estimate it, their applicability is severely restricted by the requirement for a known illumination spectrum. In this work, we present a single-image estimation method using fluorescence with no requirement for a known illumination spectrum. Under different illuminations, the spectral distributions of fluorescence emitted from the same material remain unchanged up to a certain scale. Thus, a camera’s response to the fluorescence would have the same chromaticity. Making use of this chromaticity invariance, the camera spectral sensitivity can be estimated under an arbitrary illumination whose spectrum is unknown. Through extensive experiments, we proved that our method is accurate under different illuminations. Moreover, we show how to recover the spectra of daylight from the estimated results. Finally, we use the estimated camera spectral sensitivities and daylight spectra to solve color correction problems.