[1] DUAN Y N,CHEN W, WANG M ZH. A relative radiometric correction method for airborne image using outdoor calibration and image statistics ［J］. IEEE Transaction on Geoscience and Remote Sensing, 2014, 52(8): 5164-5174.

[2] YANG L, LI G J, WANG L R. Registration between multiple sequences for scene construction［J］. Opt. Precision Eng., 2015, 23(2): 557-565. (in Chinese)

[3] WANG J B, ZHU M. Realtime image registration based on dictionary feature descriptor［J］. Opt. Precision Eng., 2014, 22(6): 1613-1621. (in Chinese)

[4] ZARAGOZA J, CHIN T J, TRAN Q H. As-projective-as-possible image stitching with moving DLT ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence,2014, 36(7): 1285-1298.

[5] WANG F, CHENG M, CHEN X P. An RGB-D image alignment algorithm for robotic mapping in indoor environments［J］. ROBOT, 2015, 37(2): 129-135. (in Chinese)

[6] HARTLEY R, ZISSERMAN A. Multiple View Geometry in Computer Vision［M］. 2nd Edition. Cambridge: Cambridge University Press, 2004,87-129.

[7] HARTLEY R. In defense of the eight-point algorithm ［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(6): 580-593.

[8] FISCHLER M A,BOLLES R C. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography ［J］. Communications of the ACM, 1981, 24(6): 381-395.

[9] ROUSSEEUW P J. Least median of squares regression ［J］. Journal of the American Statistical Association, 1984, 79(388): 871-880.

[10] YAN Q, XU Y, YANG X K. HEASK: robust homography estimation based on appearance similarity and keypoint correspondences ［J］. Pattern Recognition, 2014, 47(1): 368-387.

[11] MOU W, WANG H, SEET G. Robust homography estimation based on nonlinear least squares optimization ［J］. Mathematical Problems in Engineering, 2014: 372-377.

[12] CHUM O, MATAS J. Matching with prosa progressive sample consensus ［C］. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 2005,220-226.

[13] RAGURAM R,FRAHM J M,POLLEFEYS M. A comparative analysis of ransac techniques leading to adaptive real-time random sample consensus ［C］. European Conference on Computer Vision, 2008,500-513.

[14] TORR P,ZISSERMAN A. Mlesac: a new robust estimator with application to estimating image geometry ［J］. Computer Vision and Image Understanding, 2000, 78(1): 138-156.

[15] TORR P. Bayesian model estimation and selection for epipolar geometry and generic manifold fitting［J］. International Journal of Computer Vision, 2002, 50(1): 35-61.

[16] LEBEDA K, MATAS J, CHUM O. Fixing the locally optimized RANSAC ［C］. Proceeding of the British Machine Vision Conference, Guildford, ENGLAND, 2012.

[17] LOWE D. Distinctive image features from scale-invariant keypoints ［J］. International Journal of Computer Vision, 2004, 60(2): 91-110.

[18] BAY H, TUYTELAARS T. SURF: Speeded Up Robust Features［C］. European Conference on Computer Vision, Graz, Austria, 2006: 404-417.

[19] STEELE R MATT, CHRISTOPHERh JAYNES. Feature uncertainty arising from covariant image noise［C］. IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, 2005: 1063-1070.

[20] ABDEL-HAKIM A E,FARAG A A. Farag. A novel stability quantification of detected interest points in scale-space［C］. International Conference on Pattern Recognition, Tampa, FL, 2008,124-127.

[21] BEMHARD Z, PIERRE F G, FLORIAN S,et al.. Estimation of location uncertainty for scale invariant feature points［C］. British Machine Vision Conference, London, United Kingdom, 2009,1-12.