A new stereo matching algorithm based on improved four-moded census transform and adaptive cross pyramid model

Abstract

Stereo matching is still very challenging in terms of depth discontinuity, occlusions, weak texture regions, and noise resistance. To address the problems of poor noise immunity of local stereo matching and low matching accuracy in weak texture regions, a stereo matching algorithm (iFCTACP) based on improved four-moded census transform (iFCT) and a novel adaptive cross pyramid (ACP) structure were proposed. The algorithm combines the improved four-moded census transform matching cost with traditional measurement methods, which allows better anti-interference performance. The cost aggregation is performed on the adaptive cross pyramid structure, a unique structure that improves the traditional single mode of the cross. This structure not only enables regions with similar color and depth to be connected but also achieves cost smoothing across regions, significantly reducing the possibility of mismatch due to inadequate corresponding matching information and providing stronger robustness to weak texture regions. Experimental results show that the iFCTACP algorithm can effectively suppress noise interference, especially in illumination and exposure. Furthermore, it can markedly improve the error matching rate in weak texture regions with better generalization. Compared with some typical algorithms, the iFCTACP algorithm exhibits better performance whose average mismatching rate is only 3.33%.

Keywords

• stereo matching
• improved fct
• cross pyramid
• adaptive window