Sub-pixel stereo matching

The obtention of 3D information from two images requires the perfect control of a long chain of algorithms: internal and external calibration, stereo-rectification, correlation, and finally 3D reconstruction. In this paper we focus on the improvement of the correlation step for small baseline stereo. In that setting a very strong sub-pixel accuracy is possible. This accuracy is also necessary to obtain high resolution urban maps in geographic information systems. We show that if the images are carefully taken, then the disparity map in stereo-rectified images can be computed for a majority of image points to a 1/20 pixel precision under realistic noise conditions. Experiments on the Middlebury benchmark also stress the need for a methodology to create reliable ground truths.