A Census Transform Based Stereo Matching Algorithm Using Variable Support-Weight

Aiming at solving the problem of low accuracy of matching algorithm by typical Census transform, a stereo matching algorithm using variable support-weight based on modified census transform is proposed. On the basis of analyzing the defects of traditional Census transform, a modified Census transform algorithm was developed using average value of minimum evenness sub-area as a reference instead of the center pixel intensity, which enhanced the robustness of the algorithm. The matching accuracy was improved by weighting the average value and the standard deviation of Hamming distances in a region. By means of left-right checking and occlusion filling, the final disparity map could be acquired at last. Experiment results indicate that the robustness of proposed algorithm is enhanced. Accurate disparity could be obtained even in the depth-discontinuities regions.