Most illuminant estimation algorithms work with the assumption of one specific type of the light source (e.g. point light source or directional light source). This assumption brings up two main limitations which significantly restrict the applicability of the algorithms: First, the knowledge about the type of the light source presented in the scene is needed a priori; second, it can not handle complex scenes where multiple different types of light sources co-exist. To overcome these limitations, we remove the assumption about the source type and develop a general light source model for all different types of light sources. Based on this general light source model, we propose a unified framework to estimate multiple illuminants of different types. Within the framework, we use an experiment setup where a calibration sphere with a specular surface is utilized to probe the scene illuminants and a novel ray tracing and matching algorithm is devised to estimate the light source parameters. ...