Robust Contrast Invariant Stereo Correspondence

A stereo pair of cameras attached to a robot will inevitably yield images with different contrast. Even if we assume that the camera hardware is identical, due to slightly different points of view, the amount of light entering the two cameras is also different, causing dynamically adjusted internal parameters such as aperture, exposure and gain to be different. Due to the difficulty of obtaining and maintaining precise intensity or color calibration between the two cameras, contrast invariance becomes an extremely desirable property of stereo correspondence algorithms. The problem of achieving point correspondence between a stereo pair of images is often addressed by using the intensity or color differences as a local matching metric, which is sensitive to contrast changes. We present an algorithm for contrast invariant stereo matching which relies on multiple spatial frequency channels for local matching. A fast global framework uses the local matching to compute the correspondences and find the occlusions. We demonstrate that the use of multiple frequency channels allows the algorithm to yield good results even in the presence of significant amounts of noise.