Laser & Optoelectronics Progress, Volume. 58, Issue 2, 0215008(2021)
Stereo Matching Algorithm Based on Improved Census Transform and Gradient Fusion
Binocular stereo matching transforms plane vision into three-dimensional stereo vision based on the parallax principle, which is one of the core steps of three-dimensional reconstruction. Aiming at the problems of local stereo matching algorithm in the depth discontinuity, low matching accuracy in weak texture areas, and easy to be interfered by factors such as light and noise, an improved stereo matching algorithm is proposed in this paper. First, in the cost calculation stage, the improved Census cost and the gradient cost are fused, and the guided filtering algorithm is used to perform multi-scale cost aggregation on the image; then, the winner-take-all algorithm is used to calculate the initial disparity; finally, the left-right consistency detection, middle value filtering performs disparity post-processing to obtain the final disparity image. Experimental results show that the average mistake match rate of the algorithm on the Middlebury2.0 test platform is 5.11%, and it has good robustness and practicability.
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Hong Xiao, Chuan Tian, Yi Zhang, Bo Wei, Jiaqi Kang. Stereo Matching Algorithm Based on Improved Census Transform and Gradient Fusion[J]. Laser & Optoelectronics Progress, 2021, 58(2): 0215008
Category: Machine Vision
Received: Jul. 1, 2020
Accepted: Jul. 22, 2020
Published Online: Jan. 11, 2021
The Author Email: Tian Chuan (zgtchuan@qq.com)