Color matching and illumination estimation for urban scenes

Photographs taken of the same scene often look very different, due to various conditions such as the time of day, the camera characteristics, and subsequent processing of the image. Prime examples are the countless photographs of urban centers taken throughout history. In this paper we present an approach to match the appearance between photographs that removes effects such as different camera settings, illumination, fading ink and paper discoloration over time, and digitization artifacts. Global histogram matching techniques are inadequate for appearance matching of complex scenes where background, light, and shadow can vary drastically, making correspondence a difficult problem. We alleviate this correspondence problem by registering photographs to 3D models of the scene. In addition, by estimating the calendar date and time of day, we can additionally remove the effect of drastic lighting and shadow differences between the photographs. We present results for the case of urban scenes, and show that our method allows for realistic visualizations by blending information from multiple photographs without color-matching artifacts.