Multilevel enhancement and detection of stereo disparity surfaces

AbstractThe problem of stereo vision has been of increasing interest to the computer vision community over the past decade. This paper presents a new computational framework for matching a pair of stereo images arising from viewing the same object from two different positions. In contrast to previous work, this approach formulates the matching problem as detection of a “bright”, coherent disparity surface in a 3D image called the spatio-disparity space (SDS) image. The SDS images represents the goodness of each and every possible match.A nonlinear filter is proposed for enhancing the disparity surface in the SDS image and for suppressing the noise. This filter is used to construct a hyperpyramid representation of the SDS image. Then the disparity surface is detected using a coarse-to-fine control structure. The proposed method is robust to photometric and geometric distortions in the stereo images, and has a number of computational advantages. It produces good results for complex scenes