Fluctuations of disparity space image for stereo matching in untextured regions

Allocating the disparities to the untextured regions in stereo image still remains an intractable and challenging problem. In this paper, we present a novel local stereo matching algorithm for large untextured regions. The core ideas behind our method are from two aspects: 1) the fluctuating characteristics of cost volume are first exploited to distinguish ambiguous and unambiguous image regions; 2) the matching costs of pixels in ambiguous regions are regularized with an adaptive cost aggregation. The WTA strategy is performed on the regularized cost volume followed by postprocessing to obtain accurate disparity map. Comparative experiments are conducted on different data sets and the results demonstrate the effectiveness and efficiency of our method.