Unsupervised Simultaneous Registration and Exposure Correction

Early approaches to building mosaics by composing photographic images, assume the input images have similar exposures. Since this is unlikely to happen in practice, it became common to compensate for different exposures in the blending step, after the images have been registered, or aligned. However, registration methods usually assume brightness constancy and fail to align images with different exposures. Recent approaches to this problem lead to computationally complex solutions that require either robust statistics or nonlinear optimization. In this paper we propose a computationally simple method to jointly estimate the registration parameters and the parameters describing the exposure correction, directly from the image intensity values. We obtain closed-form solutions for the estimates of the exposure parameters. This enables the derivation of a simple two-step iterative algorithm to minimize the global cost. Our experiments show that this algorithm succeeds to register real images exhibiting simultaneously very distinct orientations and exposures.