MULTILEVEL ENHANCEMENT AND DETECTION OF STEREO DISPARITY SURFACES

The problem of stereo vision has been of increasing interest to the co mputer vision community over the past decade. This paper presents a ne w computational framework for matching a pair of stereo images arising from viewing the same object from two different positions. In contras t to previous work, this approach formulates the matching problem as d etection of a ''bright'', coherent disparity surface in a 3D image cal led the spatio-disparity space (SDS) image. The SDS images represents the goodness of each and every possible match. A nonlinear filter is p roposed for enhancing the disparity surface in the SDS image and for s uppressing the noise. This filter is used to construct a hyperpyramid representation of the SDS image. Then the disparity surface is detecte d using a coarse-to-fine control structure. The proposed method is rob ust to photometric and geometric distortions in the stereo images, and has a number of computational advantages. It produces good results fo r complex scenes.