A new correlation criterion based on gradient fields similarity

Correlation based methods are a common tool for the correspondence problem. They are able to perform a dense point-to-point matching between two images, but post-processing is often necessary to improve the results. In this paper we propose a new correlation measure using the gradient vector fields of the images. We compare our method to classical correlation measures based on the grey levels. The new method gives better results than others when it is applied on random dot stereograms and on real images