This work is licensed under the Creative Commons Attribution 4.0 International License.
Ma Songde, Zhang Zhengyou. Computer Vision-Fundamentals of Computing Theory and Algorithms (First Edition) [M]. Beijing: Science Press, 1998. (in Chinese).Search in Google Scholar
Wheatstone C.. Contributions to the physiology of vision.—Part the first. on some remark-able, and hitherto unobserved, phenomena of binocular vision [J]. Philosophical Transactions of the Royal Society of London, 1994, 49(128).Search in Google Scholar
Dai Zongxian. Research on 3D reconstruction and measurement technology based on binocular vision [D]. Chongqing University, 2014. (in Chinese).Search in Google Scholar
Xu Zhou Peng, Yang Chaolin. On-line detection method of tiny defects on the surface of sheet metal strip based on photometric stereology [J]. Journal of Mechanical Engineering. 2013, 49(04). (in Chinese).Search in Google Scholar
He Qing. Research on 3D reconstruction technology based on binocular stereo vision [D]. Huazhong University of Science and Technology. (in Chinese).Search in Google Scholar
Wang Peng. Research on target recognition and location based on binocular vision [D]. Yanshan University, 2020. (in Chinese).Search in Google Scholar
Sdiri B, Kaaniche M, Cheikh F A, et al. Efficient enhancement of stereo endoscopic images based on joint wavelet decomposition and binocular combination [J]. IEEE transactions on medical imaging, 2018.Search in Google Scholar
Cao Jing. Research and implementation of key technologies in binocular stereo vision system [D]. Xi ’an University of Science and Technology, 2019. (in Chinese).Search in Google Scholar
Rosten E, Drummond T. Machine Learning for High-Speed Corner Detection. European Conference on Computer Vision. Springer-Verlag, 2006:430-443P.Search in Google Scholar
Xin Yang. Research on the key technologies of computer-generated holographic 3D display [D]. Soochow University, 2018. (in Chinese).Search in Google Scholar
Yu Daoyin. Fundamentals of Engineering Optics [M]. Beijing: China Machinery Industry Press, 2011. (in Chinese).Search in Google Scholar
Cassisa C.. Local vs global energy minimization methods: application to stereo match-ing [A]. In: IEEE International Conference on Progress in Informatics and Computing [C],2010: 678–683.Search in Google Scholar
Kuzmin A., Mikushin D., Lempitsky V. End-to-End learning of cost-volume aggregationfor real-time dense stereo [A]. In: IEEE International Workshop on Machine Learning forSignal Processing [C], 2017: 1–6.Search in Google Scholar
Lv eryang. Research on a design method of relay framing optical system [D]. Tianjin University, 2012. (in Chinese).Search in Google Scholar
Lowe D G. Distinctive Image Features from Scale-Invariant Keypoints. International Journal of Computer Vision, 2004, 60(2):91-110P.Search in Google Scholar
Ke Y, Sukthankar R. PCA-SIFT: a more distinctive representation for local image descriptors//IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society, 2004:28-43P.Search in Google Scholar
Shi Erying, Zhu Jiaqun, Yang Changchun. Image forgery detection algorithm based on nearest neighbor search coupled with nearest neighbor loss clustering. Packaging Engineering, 2018(5):185-190. (in Chinese).Search in Google Scholar
Suo Chunbao, Yang Dongqing, Liu Yunpeng. Comparison of SIFT, SURF, BRISK, ORB and FREAK algorithms from various angles [J]. Beijing Surveying and Mapping, 2014, 04(06). (in Chinese).Search in Google Scholar
Ghani A S A, Isa N A M. Enhancement of low quality underwater image through integrated global and local contrast correction [J]. Applied Soft Computing, 2015, 37: 332-344.Search in Google Scholar
Ghani A S A, Isa N A M. Automatic system for improving underwater image contrast and color through recursive adaptive histogram modification [J]. Computers and electronics in agriculture, 2017, 141: 181-195.Search in Google Scholar