基于改进Census变换的鲁棒立体匹配算法

doi:10.3969/j.issn.1000-1158.2023.05.04

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Abstract Aiming at the problems of the noise and illumination sensitive and with high false matching radio in the weak texture region of the local matching algorithm, an robust stereo matching algorithm for improved Census transform and adaptive parameter-guided filter is proposed. The hue, saturation, value(HSV) channel value is used to calculate the cost, which has higher robustness to noise and illumination changes. In the support window, the distance weighting and color weighting are used to obtain the reference value of the census transform respectively. The two costs are fused to improve the stability of the single pixel matching cost. The kurtosis adaptive regularization parameter is used on the guide filter for cost aggregation. Finally, the disparity map is obtained by disparity calculation. The matching experiment is carried out on the image pairs provided by Middlebury database on the VS2017. The average error matching rate of the proposed algorithm of standard image, noisy image and illumination change image is 7.80%, 10.72% and 9.89% respectively. The results show that the algorithm can reduce the false matching ratio and better adapt to the changes of noise and illumination.

Key words： metrology stereo matching image processing improved census transform cost compute;adaptive parameter false matching ratio

Received: 12 October 2022 Published: 18 May 2023

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TB96

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	Articles by authors
	QIAO Jing-hui
	HAN Yu-ming
	ZHANG Xiao-han

Cite this article:

QIAO Jing-hui,HAN Yu-ming,ZHANG Xiao-han. Robust Stereo Matching Algorithm Based on Improved Census Transform[J]. Acta Metrologica Sinica, 2023, 44(5): 694-700.

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http://jlxb.china-csm.org:81/Jwk_jlxb/EN/10.3969/j.issn.1000-1158.2023.05.04 OR http://jlxb.china-csm.org:81/Jwk_jlxb/EN/Y2023/V44/I5/694

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