[1] Nichols M H, Ruyle G B, Nourbakhsh I R. Very-high-resolution panoramic photography to improve conventional rangeland monitoring[J]. Rangeland Ecology & Management, 62, 579-582(2009). http://www.cabdirect.org/abstracts/20093330595.html
[2] Ren Z G, Li X Y, Ni D W. Compact space optical system design with large relative aperture and field of view[J]. Acta Optica Sinica, 39, 0922001(2019).
[3] Li J H, Tan F L, Zeng C X et al. Optical design of an airborne camera with wide coverage and high resolution[J]. Acta Optica Sinica, 41, 0222001(2021).
[4] Lu S F, Liu Z. A fast alignment method in sequence images of multiple units train[J]. Acta Optica Sinica, 37, 0915002(2017).
[5] Kale P, Singh K R. A technical analysis of image stitching algorithm[J]. International Journal of Innovative Research in Computer and Communication Engineering, 3, 3300-3309(2015).
[6] Wu Y, Ma W P, Gong M G et al. A novel point-matching algorithm based on fast sample consensus for image registration[J]. IEEE Geoscience and Remote Sensing Letters, 12, 43-47(2015). http://smartsearch.nstl.gov.cn/paper_detail.html?id=5899bc22f29ca744cae8c2d6956e0b9f
[7] Lowe D G. Distinctive image features from scale-invariant keypoints[J]. International Journal of Computer Vision, 60, 91-110(2004). http://doi.ieeecomputersociety.org/resolve?ref_id=doi:10.1023/B:VISI.0000029664.99615.94&rfr_id=trans/tp/2008/10/ttp2008101683.htm
[8] Bay H, Ess A, Tuytelaars T et al. Speeded-up robust features (SURF)[J]. Computer Vision and Image Understanding, 110, 346-359(2008). http://www.sciencedirect.com/science/article/pii/S1077314207001555
[9] Li Z Y, Tian Y, Chen F J et al. Aerial image stitching algorithm for unmanned aerial vehicles based on improved ORB and PROSAC[J]. Laser & Optoelectronics Progress, 56, 231003(2019).
[10] Yang Q N, Ma T L, Yang C K et al. RANSAC image matching algorithm based on optimized sampling[J]. Laser & Optoelectronics Progress, 57, 101104(2020).
[11] Fischler M A, Bolles R C. Random sample consensus[J]. Communications of the ACM, 24, 381-395(1981).
[12] Sattler T, Leibe B, Kobbelt L. SCRAMSAC: improving RANSAC’s efficiency with a spatial consistency filter[C]. //2009 IEEE 12th International Conference on Computer Vision, September 29-October 2, 2009, Kyoto, Japan, 2090-2097(2009).
[13] Torr P H S, Zisserman A. MLESAC: a new robust estimator with application to estimating image geometry[J]. Computer Vision and Image Understanding, 78, 138-156(2000). http://dl.acm.org/citation.cfm?id=344583
[14] Chum O, Matas J, Kittler J. Locally optimized RANSAC[M]. //Michaelis B, Krell G. Pattern recognition. Lecture notes in computer science, 2781, 236-243(2003).
[15] Lebeda K, Matas J, Chum O. Fixing the locally optimized RANSAC[C]. //Procedings of the British Machine Vision Conference, September 3-7, 2012, Surrey, 1-11(2012).
[16] Lattanzi S, Lavastida T, Moseley B et al. Online scheduling via learned weights[M]. //Chawla S. Proceedings of the fourteenth annual ACM-SIAM symposium on discrete algorithms, 1859-1877(2020).
[17] Zhu Q, Wu B, Xu Z X. Seed point selection method for triangle constrained image matching propagation[J]. IEEE Geoscience and Remote Sensing Letters, 3, 207-211(2006). http://ieeexplore.ieee.org/document/1621080
[18] Mikolajczyk K, Schmid C. A performance evaluation of local descriptors[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27, 1615-1630(2005).
[19] Heinly J, Dunn E, Frahm J M. Comparative evaluation of binary features[M]. //Fitzgibbon A, Lazebnik S, Perona P, et al. Computer vision-ECCV 2012. Lecture notes in computer science, 7573, 759-773(2012).
[20] Ma J Y, Zhao J, Jiang J J et al. Locality preserving matching[J]. International Journal of Computer Vision, 127, 512-531(2019).
[21] Cai Z P, Chin T J, Le H et al. Deterministic consensus maximization with biconvex programming[EB/OL]. (2018-07-25)[2020-08-20]. https: //arxiv.org/abs/1807.09436
