Abstract: This paper presents a novel disparity estimation algorithm based on the gradient and Markov Random Field (MRF) model. First, the block matching algorithm combining gray and gradient information is adopted to obtain an initial disparity field. Second, an order matching constraint is applied to detect cross regions in the disparity-map. Finally, the erroneously matched blocks are corrected iteratively by MRF-based causality prediction to achieve a more accurate disparity field. Experimental results show that the proposed algorithm achieves a PSNR gain(about 1.2~1.8dB) as compared to the conventional block-based method and its calculating time is less than 1s.

Key words: stereo match, disparity field, gradient, cross detection, Markov random field