Stochastic Approach to Separate Diffuse and Specular Reflections

Abstract

This paper presents separation of specular and diffuse reflection components from an image pair. The proposed approach is based on the dichromatic reflectance model and Markov random field models. The proposed method estimates specular and diffuse components by minimizing observation color noise and prior potential of specular reflectance. The specular reflection component is modelled as an MRF and estimated in maximum a posteriori framework. This paper proposes likelihood term of specular component and the prior model of specular reflectance based on Phong's shading. Some experiments show that the proposed approach separates the specular and diffuse reflection components effectively. The separated specular components can be utilized in image-based lighting which renders a scene with virtual lighting sources.