Image registration under poor illumination using calibrated cameras

Abstract

Image registration is basic step in image fusion and in many 2D applications. Registering the 2D image with recent robust algorithms like SIFT (Scale invariant Feature Transform) works well in most situations. However, registering the 2D images under poor illumination is a challenging problem. In several situations, conventional registration algorithms like SIFT fail to register the images. Aside from poor illumination conditions, images involving too much symmetry can also pose registration difficulties for conventional methods. In our approach, we overcome these limitations by using the knowledge of the intrinsic camera parameters together with a new registration method to help in registering the features (lines) between the two overlapping images. Our approach is useful especially in registering the images taken by different sensors or the same sensor at different times under poor illumination conditions. Experiments are tested on real world environments.