Estimation of spectral distribution of scene illumination from a single image

This article proposes an illuminant estimation algorithm that estimates the spectral power distribution of an incident light source from a single imag e. The proposed illumination recovery procedure has two phases. First, the surface spectral reflectances are recovered. In this case, the surface spec tral reflectances recovered are limited to the maximum achromatic region (M AR) which is the most achromatic and highly bright region of an image, afte r applying intermediate color constancy process using a modified gray-world algorithm. Next, the surface reflectances of the maximum achromatic region are estimated using the principal component analysis method along with a s et of given Munsell samples. Second, the spectral distribution of reflected lights of MAR is selected from the spectral database. That is, a color dif ference is compared between the reflected lights of the MAR and the spectra l database, which is the set of reflected lights built by the given Munsell samples and a set of illuminants. Then the closest colors from the spectra l database are selected. Finally, the illuminant of an image can be calcula ted dividing the average spectral distributions of reflected lights of MAR by the average surface reflectances of the MAR. In order to evaluate the pr oposed algorithm, experiments with artificial and real captured color-biase d scenes were performed and numerical comparison examined. The proposed met hod was effective in estimating the spectral distribution of the given illu minants under various illuminants and scenes without white points.