[1] Lu Di, Lin Xue. A local stereo matching algorithm based on the combination of multiple similarity measures[J]. Robot, 38, 1-7(2016).
[2] Scharstein D, Szeliski R. A taxonomy and evaluation of dense two-frame stereo correspondence algorithms[J]. International Journal of Computer Vision, 47, 7-42(2002). http://ieeexplore.ieee.org/xpls/icp.jsp?arnumber=988771
[3] Zhang Qiang, Lu Shiqiang, Li Haibin et al. Research on underwater stereo matching method based on color segmentation[J]. Acta Optica Sinica, 36, 0815001(2016).
[4] Li Q W, Ma Y P, He F J et al. Bionic vision-based intelligent power line inspection system[J]. Computational and Mathematical Methods in Medicine, 2017, 4964287(2017). http://pubmedcentralcanada.ca/pmcc/articles/PMC5288559/
[5] Bleyer M, Gelautz M. Simple but effective tree structures for dynamic programming-based stereo matching[C]. Third International Conference on Computer Vision Theory and Applications, 415-422(2008).
[6] Klaus A, Sormann M, Karner K. Segment-based stereo matching using belief propagation and a self-adapting dissimilarity measure[C]. 18
th International Conference on Pattern Recognition, 3, 15-18(2006).
[7] Wang H Q, Wu M, Zhang Y B et al. Effective stereo matching using reliable points based graph cut[C]. Visual Communications and Image Processing, 1-6(2013).
[8] Zhu Shiping, Li Zheng. A stereo matching algorithm using improved gradient and adaptive window[J]. Acta Optica Sinica, 35, 0110003(2015).
[9] Lee J, Jun D, Eem C et al. Improved census transform for noise robust stereo matching[J]. Optical Engineering, 55, 063107(2016). http://adsabs.harvard.edu/abs/2016OptEn..55f3107L
[10] Mei X, Sun X, Zhou M C et al. On building an accurate stereo matching system on graphics hardware[C]. IEEE International Conference on Computer Vision Workshops, 21, 467-474(2011).
[11] Shi Hua, Zhu Hong. Stereo matching based on adaptive matching windows and muti-feature fusion[J]. Pattern Recognition and Artificial Intelligence, 29, 193-202(2016).
[12] Zhang K, Lu J B, Lafruit G. Cross-based local stereo matching using orthogonal integral images[J]. IEEE Transactions on Circuits & Systems for Video Technology, 19, 1073-1079(2009). http://ieeexplore.ieee.org/document/4811952/
[13] Yao P, Zhang H, Xue Y B et al. Iterative color-depth MST cost aggregation for stereo matching[C]. IEEE International Conference on Multimedia and Expo, 1-6(2016).
[14] Zhu Shiping, Yan Lina, Li Zheng. Stereo matching algorithm based on improved census transform and dynamic programming[J]. Acta Optica Sinica, 36, 0415001(2016).
[16] Hu T B, Qi B, Wu T J et al. Stereo matching using weighted dynamic programming on a single-direction four-connected tree[J]. Computer Vision and Image Understanding, 116, 908-921(2013). http://www.sciencedirect.com/science/article/pii/S1077314212000641
[17] Hosni A, Rhemann C, Bleyer M et al. Fast cost-volume filtering for visual correspondence and beyond[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 35, 504-511(2012). http://dl.acm.org/citation.cfm?id=2191908
[18] Cheng F Y, Zhang H, Sun M G et al. Cross-trees, edge and superpixel priors-based cost aggregation for stereo matching[J]. Pattern Recognition, 48, 2269-2278(2015). http://pubmedcentralcanada.ca/pmcc/articles/PMC4448781/
[19] Wang L Q, Liu Z, Zhang Z H. Feature based stereo matching using two-step expansion[J]. Mathematical Problems in Engineering, 2014, 452803(2014). http://www.researchgate.net/publication/287692188_Feature_Based_Stereo_Matching_Using_Two-Step_Expansion
[20] Wang L, Yang R G, Gong M L et al. Real-time stereo using approximated joint bilateral filtering and dynamic programming[J]. Journal of Real-Time Image Processing, 9, 447-461(2014). http://link.springer.com/article/10.1007/s11554-012-0275-4