Research on Image Data Matching Method Based on Infrared Spectrum Technology of UAV
TAN Xiang1, 2, MAO Hai-ying2, ZHI Xiao-dong3, HU Xing-bang1, MA Ai-nai1, YAN Lei1*
1. Beijing Key Lab of Spatial Information Integration &3S Application, Peking University, Beijing 100871, China
2. Specialized Forces College of the Chinese Armed Police Force, Beijing 102202, China
3. Feima Robotics Co., Ltd., Shenzhen 518000, China
Abstract：UAV loading infrared/near-infrared spectroscopy on regional image acquisition load has become an important field of remote sensing technology, through classifying the position information of the portable image, and getting the vegetation cover, temperature index and a series of factors. In this paper, we used FREE BIRD low altitude unmanned aerial vehicle (UAV) to mount Tetracam- infrared camera (3 million 100 thousand pixels) to get the image of a river in Xinjiang, Manasi. In order to get more accurate vegetation temperature and other factors, we needed UAV infrared/near infrared image registration, through the optimization of SIFT, detection of outliers and RANSAC parameters, to obtain reliable matching results. After the matching algorithm of the image ,the original image of the error ratio were below 60%, which was one of the innovations of this paper to meet the needs of the application. After registering the images, the images were spliced, and the infrared images were spliced according to the degree of overlap of the course of not less than 60%, while the probability of the adjacent overlap was not less than 50%. At the same time, this paper compared the SIFT and SUFT two kinds of algorithms, using FLIR sensor SIFT algorithm and improved optimization to obtain 1 600 thermal infrared image matching and image inversion of ground by utilization of synchronous measurement data. We used ENVI software to carry out the inversion of vegetation coverage temperature inversion and inversion vegetation map to get the single image and the infrared image of the study area. The algorithm model is more optimized through the comparison of the two algorithms, while the model of regression analysis and test of accuracy, the correlation coefficient R2 of the model is 0.767, and accuracy is 81.51% with higher model precision. This model provides theoretical and practical basis for the registration and extraction of inversion of UAV infrared image.
谭 翔，毛海颖，支晓栋，胡兴帮，马蔼乃，晏 磊. 基于无人机红外光谱技术的影像数据匹配方法研究[J]. 光谱学与光谱分析, 2018, 38(02): 413-417.
TAN Xiang, MAO Hai-ying, ZHI Xiao-dong, HU Xing-bang, MA Ai-nai, YAN Lei. Research on Image Data Matching Method Based on Infrared Spectrum Technology of UAV. SPECTROSCOPY AND SPECTRAL ANALYSIS, 2018, 38(02): 413-417.
[1] Tuytelaars T, Mikolajczyk K. Computer, Graphics and Vision, 2008，3(3): 177.
[2] Calonder M, Lepetit V, Strecha C, et al. Brief: Binary Robust Independent Elementary Features. Computer Vision—ECCV 2010. Springer Berlin Heidelberg, 2010. 778.
[3] Rublee E, Rabaud V, Konolige K, et al. ORB: an Efficient Alternative to SIFT or SURF. Computer Vision (ICCV), 2011 IEEE International Conference on. IEEE, 2011. 2564.
[4] Matas J, Chum O, Urban M, et al. Image and Vision Computing, 2004, 22(10): 761.
[5] Morel J M, Yu G. SIAM Journal on Imaging Sciences, 2009, 2(2): 438.
[6] Alahi A, Ortiz R, Vandergheynst P. Freak: Fast retina Keypoint. Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on. IEEE, 2012. 510.
[7] Yi Z, Zhiguo C, Yang X. Electronics Letters, 2008, 44(2): 107.
[8] Aguilera C, Barrera F, Lumbreras F, et al. Sensors, 2012, 12(9): 12661.
[9] Meierhold N, Spehr M, Schilling A, et al. Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci, 2010, 38: 446.
[10] Sima A, Buckley S J, Kurz T H, et al. Photogrammetrie-Fernerkundung-Geoinformation, 2012, 2012(4): 443.
[11] Wang W, Cao T, Liu S. J. of the Indian Society of Remote Sensing, 2015, 20(1): 71.
[12] Herbert Bay, Tinne Tuvtellars，Luc Van Gool. SURF: Speeded Up Robust Features. European Conference on Computer Vision，2006. 404.
[13] May M, Turner M J. Scale Invariant Feature Transform: A Graphical Parameter Analysis. In Proceedings of the BMVC 2010 UK. Postgraduate Workshop, Aberystwyth, UK, 31 August-3 September, 2010. 1.
[14] Bendig J, Bolten A, Bennertz S, et al. Remote Sensing, 2014, 6(11): 10395.
