Aligning multi-exposed images: What are the good feature and similarity measure?
High dynamic range (HDR) imaging, a technique to synthesize a sequence of multi-exposed images, has been recently developed to reduce the dynamic range gap between captured images and real scenes. Unlike conventional cases of varying illumination in which each image is best exposed, the multi-exposed images contain severely under/over-exposed regions and have significant variations in intensity, which offer great challenge in image registration. This paper aims to identify what is the invariant representation of multi-exposed images and which similarity measure is good for these images. To this end, we present a comprehensive comparison of existing ordering features and similarity measures. Experimental results show that the mutual information is the best similarity metric, and the median threshold bitmap is the best feature in terms of accuracy and robustness.