Consistent joint photometric and geometric image registration

In this paper, we derive a novel robust image alignment technique that performs joint geometric and photometric registration in the total least square sense. The main idea is to use the total least square metrics instead of the ordinary least square metrics, which is commonly used in the literature. While the OLS model indicates that the target image may contain noise and the reference image should be noise-free, this puts a severe limitation on practical registration problems. By introducing the TLS model, which allows perturbations in both images, we can obtain mutually consistent parameters. Experimental results show that our method is indeed much more consistent and accurate in presence of noise compared to existing registration algorithms.