Illumination Estimation from Shadow Borders

In this paper we discuss illumination estimation from a single image in general scenes and associate it with the existence of shadow edges, avoiding several pitfalls that burden previous illumination estimation approaches, which rely on associating a parametrization of illumination with the per pixel intensity of shadows or shading. We show a way to couple shadow and illumination estimation, relying only on the subset of shadow edges that is relevant to the provided geometry. In our approach, illumination estimation is posed as the minimization of an energy function that penalizes the matching between the expected shadow outline and observed image edges. Minimizing this energy function is strongly tied to selecting the appropriate set of potential shadow edges in the image. Our approach leads to an illumination estimation algorithm that performs on par with or better than the state of the art, even when scene geometry knowledge is limited, while having much lower computational complexity than state-of-the-art methods. We demonstrate the effectiveness of this approach both with quantitative results on synthetic data and qualitative evaluation on real images