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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Stereo Matching with Improved ADCensus Transform and Adaptive Window (IEEE/CSAA GNCC)*


    Contributors:
    Li, Yibo (author) / Xiong, Zhi (author) / Wan, Zhong (author) / Liu, Jianye (author) / Yu, Yongjun (author)


    Publication date :

    2018-08-01


    Size :

    729438 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



    IEEE/CSAA AUS 2016 : 2016 IEEE/CSAA International Conference on Aircraft Utility Systems : October 10-12, 2016, Beijing, China

    IEEE/CSAA International Conference on Aircraft Utility Systems / Institute of Electrical and Electronics Engineers / Zhongguo-Hangkong-Xuehui | TIBKAT | 2016


    Research on Drogue Detection Algorithm for Aerial Refueling (IEEE/CSAA GNCC)*

    Chen, A.Guanyu / Wang, B. Xinhua / Yang, C. Tiankai et al. | IEEE | 2018


    2018 IEEE CSAA Guidance, Navigation and Control Conference (CGNCC)

    IEEE CSAA Guidance, Navigation and Control Conference / Institute of Electrical and Electronics Engineers / Zhongguo-Hangkong-Xuehui | TIBKAT | 2018



    RRT*-based Threat-Avoidance Trajectory Planning for Aircrafts (IEEE/CSAA GNCC)*

    Wei, Zhao / Liu, Li / Long, Teng et al. | IEEE | 2018