Image stitching enhancement method with symmetrical constraint of local feature points

被引：0
|
作者：
Zhong M. [1 ]
Pei J. [1 ]
机构：
[1] College of Electronics and Information Engineering, Shenzhen University, Shenzhen
来源：
Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica | 2022年 / 43卷
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
computer vision; feature point matching; image stitching; internal parameter matrix; local constraint;
D O I：
10.7527/S1000-6893.2022.26948
中图分类号：
学科分类号：
摘要：
In this paper，an image mosaic enhancement method with symmetrical constraint of local feature points is proposed. Firstly，according to the internal and external parameter matrix of the camera，the forward local constraint region of the feature points is calculated，and the set of positive matching points is obtained. Then，the inverse local constraint region is calculated，and the set of inverse matching points is obtained. The intersection in the set of forward and reverse matching point pairs is found，and the final correct matching point pair set which satisfies the symmetric constraint condition is obtained. Combining this enhancement method with the existing advanced stitching model learning algorithm，the optimal image transformation is obtained，and finally the stitched image is obtained according to the image transformation model. This method effectively overcomes the problem that the threshold of the RANSAC algorithm needs to be manually adjusted when learning different models，thus reducing the parameter sensitivity of the algorithm，and improving the image stitching accuracy. Experiments show that our method is superior to existing methods both qualitatively and quantitatively. © 2022 AAAS Press of Chinese Society of Aeronautics and Astronautics. All rights reserved.
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共 23 条
  • [11] LEE K Y, SIM J Y., Warping residual based image stitching for large parallax, 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 8195-8203, (2020)
  • [12] LI J, DENG B, TANG R, Et al., Local-adaptive image alignment based on triangular facet approximation, IEEE Transactions on Image Processing, 29, pp. 2356-2369, (2019)
  • [13] LIAO C, WANG G J, SHEN Y L, Et al., Aerial video stitching via multi-direction strips, Acta Aeronautica et Astronautica Sinica, 33, 11, pp. 2065-2073, (2012)
  • [14] YI M, GUO B L., Aerial video image registration method based on invariant features and mapping restraint, Acta Aeronautica et Astronautica Sinica, 33, 10, pp. 1872-1880, (2012)
  • [15] LU J Z, SUN F D, DONG J, Et al., Real-time mosaicking for infrared videos from an oblique sweeping camera, Chinese Journal of Aeronautics, 34, 1, pp. 309-319, (2021)
  • [16] GAO J H, KIM S J, BROWN M S., Constructing image panoramas using dual-homography warping, CVPR 2011, pp. 49-56, (2011)
  • [17] CHEN Y S, CHUANG Y Y., Natural image stitching with the global similarity prior[C], Proceedings of European Conference on Computer Vision, pp. 186-201, (2016)
  • [18] VEDALDI A, FULKERSON B., Vlfeat: An open and portable library of computer vision algorithms, Proceedings of the International Conference on Multimedia-MM'10, pp. 1469-1472, (2010)
  • [19] BOYKOV Y, KOLMOGOROV V., An experimental comparison of Min-cut/max-flow algorithms for energy minimization in vision, IEEE Transactions on Pattern Analysis and Machine Intelligence, 26, 9, pp. 1124-1137, (2004)
  • [20] BOYKOV Y, VEKSLER O, ZABIH R., Fast approximate energy minimization via graph cuts, IEEE Transactions on Pattern Analysis and Machine Intelligence, 23, 11, pp. 1222-1239, (2001)
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