Illumination estimation from specular highlight in a multi-spectral image

The reflection spectrum of an object characterizes its surface material, but for non-Lambertian scenes, the recorded spectrum often deviates owing to specular contamination. To compensate for this deviation, the illumination spectrum is required, and it can be estimated from specularity. However, existing illumination-estimation methods often degenerate in challenging cases, especially when only weak specularity exists. By adopting the dichromatic reflection model, which formulates a specular-influenced image as a linear combination of diffuse and specular components, this paper explores two individual priors and one mutual prior upon these two components: (i) The chromaticity of a specular component is identical over all the pixels. (ii) The diffuse component of a specular-contaminated pixel can be reconstructed using its specular-free counterpart describing the same material. (iii) The spectrum of illumination usually has low correlation with that of diffuse reflection. A general optimization framework is proposed to estimate the illumination spectrum from the specular component robustly and accurately. The results of both simulation and real experiments demonstrate the robustness and accuracy of our method.