Color Balancing for Change Detection in Multitemporal Images

Abstract

Automatic color balancing approaches for different applications have been studied by different research communities in the past decade. However, in this paper we address color balancing for the purpose of change detection. Images of a scene taken at different times may have variations in lighting and structural content. For such multitemporal images, an ideal color correction approach should be effective at transferring the color palette of the source image to the target image for the unchanged areas while being able to transfer the global color characteristics for the changed area without creating visual artifacts. Towards this goal, we propose a new local color balancing approach that uses adaptive windowing. We evaluated the proposed method against other state-of-the-art ones using a database consisting of aerial image pairs. The test image pairs were taken at different times, under different lighting conditions, and with different scene geometries and camera positions. On this database, our proposed approach outperformed other state-of-the-art algorithms.