A Probabilistic Framework for Complex Wavelet Based Image Registration

The aim of this article is to introduce a computationally tractable mathematical model of the relation between the complex wavelet coefficients of two different images of the same scene. Because the two images are acquisitioned at distinct times, from distinct viewpoints, or by distinct sensors, the relation between the wavelet coefficients is far too complex to handle it in a deterministic fashion. This is why we consider adequate and present a probabilistic model for this relation. We further integrate this probabilistic framework in the construction of a new image registration algorithm. This algorithm has subpixel accuracy, and is robust to noise and to a large class of local variations like changes in illumination and even occlusions. We empirically prove the properties of this algorithm using synthetic and real data.