Stereo Matching with Improved ADCensus Transform and Adaptive Window (IEEE/CSAA GNCC)
Yibo Li, Zhi Xiong, Zhong Wan, Jianye Liu, Yongjun Yu · 2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC) · 2018
To solve the problem that traditional local stereo matching algorithm is susceptible to illumination and environmental noise, ADCensus transformation is used to calculate the initial matching cost, and adaptive window algorithm is used to construct different aggregation windows for regions with different texture degrees to improve the matching accuracy. A regional voting optimization algorithm based on confidence map is proposed. Combined with multiple optimization steps, the mis-matching point and the matching error rate of the disparity map is effectively reduced. The proposed algorithm is tested using the Middlebury standard image set. The results show that the algorithm can calculate the disparity value accurately.