Computer Science

Computer Science ›› 2021, Vol. 48 ›› Issue (8): 134-138.doi: 10.11896/jsjkx.200600140

• Computer Graphics & Multimedia • Previous Articles     Next Articles

Study on Aerial Image Fast Registration from UAV

HU Yu-cheng, RUI Ting, YANG Cheng-song, WANG Dong, LIU Xun   

  1. College of Field Engineering,Army Engineering University of PLA,Nanjing 210007,China
  • Received:2020-06-22 Revised:2020-09-27 Published:2021-08-10
  • About author:HU Yu-cheng,born in 1995,postgra-duate.His main research interests include image processing,pattern recognition and artificial intelligence.(361721310@qq.com)RUI Ting,born in 1972,Ph.D,professor,Master's advisor,is a member of China Computer Federation.His main research interests include image processing,pattern recognition and artificial intelligence.
  • Supported by:
    National Natural Science Foundation of China(61671470) and National Key R&D Program of China(2016YFC0802904).

PDF (PC)

1166

Abstract: In order to improve the real time of the UAV aerial image registration,the paper analyzes the relative stability of UAV's altitude and the lack of high-frequency details in the image,proposes an improved SIFT feature point extraction algorithm and constructs a special aerial images dataset for image mosaic for experimental verification.The paper first analyzes the theoretical basis and implementation method of scale invariance of SIFT (Scale Invariant Feature Transform),and puts forward eliminating redundant performance.The measures,such as reduction of Octave and Level of Gauss pyramid,and selecting the third Level image in each Octave to detect extreme points are taken to reduce the scale of differential scale space.Lastly,the comparable experiments based on dataset with state-of-art image mosaic methods are conducted.The experimental results show that the method proposed in this paper can extract robust feature points,and the matching time is only 1/10 of the original sift,which provides technical support for real-time image mosaic of UAV.

Key words: Aerial image, Differential scale space, Image registration, Scale invariance, SIFT

CLC Number: 

  • TP391.41
[1]SHENG H,CHAO H,COOPMANS C,et al.Low-cost UAV-based thermal infrared remote sensing:Platform,calibration and applications[C]//Proceedings of 2010 IEEE/ASME International Conference on Mechatronic and Embedded Systems and Applications.IEEE,2010.
[2]WANG H F,HU Q Q,DUAN J Z.Development and applications of small airborne polarization imaging system[J].Opto-Electronic Engineering,2017(11):44-51,92.
[3]LUO L,XU Q,CHEN J,et al.UAV Image Mosaic Based on Non-Rigid Matching and Bundle Adjustment[C]//2019 IEEE International Geoscience and Remote Sensing Symposium.2019:9117-9120.
[4]WU F Q,YANG Y,PAN A N,et al.Multi-viewpoints remote sensing images registration using mixed features[J].Journal of Image and Graphics,2017,22(8):1154-1161.
[5]GILINSKY A,MANOR L Z.SIFTpack:A compact representation for efficient SIFT matching[C]//Proceedings of the 2013 IEEE International Conference on Computer Vision.IEEE,2013.
[6]BAY H,ESS A,TUYTELARRS T,et al.Speeded-Up RobustFeatures[J].Computer Vision & Image Understanding,2008,110(3):346-359.
[7]RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:An efficient alternative to SIFT or SURF[C]//2011 IEEE Internatio-nal Conference on Computer Vision.Barcelona,Spainp,2011:2564-2571.
[8]ZHEN J,QI K Y ,KAI C.SSIF T:An Improved SIFT Descriptor for Chinese Character Recognition in Complex Images[J].Information Security and Communications Privacy,2010,6:3-6.
[9]LU P,LU Q,ZHOU G L,et al.Research on Time Series Image Mosaic Method Based on Improved SIFT[J].Computer Engineering and Application,2020,56(1):196-202.
[10]MIKOLAJCZYK K,SCHMID C.A performance evalution of local descriptors[J].Computer Vision & Image Understanding,2008,11(3):404-417.
[11]YU Y,YANG N,YANG C,et al.Memristor bridge-based low pass filter for image processing[J].Journal of Systems Engineering and Electronics,2019,30(3):448-455.
[12]ZHAO A G,WANG H L,YANG X G,et al.Compressed sense SIFT descriptor mixed with geometrical feature[J].Infrared and Laser Engineering,2015,(3):1085-1091.
[13]YANG S P,CHEN J,ZHOU L,et al.Image feature matching method[J].Electronic Measurement Technology,2014,37(6):50-53.
[14]SUN S,ZENG Z.UAV image mosaic based on adaptive SIFT algorithm[C]//21st International Conference on Geoinformatics.2013:1-6.
[15]YAN C M,HAO Y F,ZHANG D,et al.An image matching method based on optimal threshold prediction under hybrid features[J].Computer Engineering and Science,2019,41(10):1803-1808.
[16]SU P F,HUANG S Q,WANG Y T ,et al.Image registration based on multi-scale corner with SIFT descriptor[J].Computer Engineering and Science,2017,39(9):1700-1705.
[17]LIU X,WANG F,WEN R S.Research of UAV Visual Navigation Based on SIFT Algorithm[J].Radio Engineering,2017,47(5):19-22.
[18]LOWE D G.Object Recognition from Local Scale-Invariant Features[C]//Proceedings of the Seventh IEEE International Conference on Computer Vision.1999:1150-1157.
[19]LOWED G.Distinctive Image Features from Scale-invariantkeypoints[J].International Journal of Computer Vision,2004,60(2):91-110.
[20]HE J,LI Y S,LU H,et al.Research of UAV Aerial Image Mosaic Based on SIFT[J].Opto-Electronic Engineering,2011,38(2):122-126.
[1] GAO Yu-tong, LEI Wei-min, YUAN Yue. Face Recognition Based on Cluster Analysis in Complex Environment [J]. Computer Science, 2020, 47(7): 111-117.
[2] HE Chao-lei,BI Xiu-li,XIAO Bin. Zernike Moment Based Approach for Local Feature Detection [J]. Computer Science, 2020, 47(2): 135-142.
[3] JIAO Yang, YANG Chuan-ying, SHI Bao. Relevance Feedback Method Based on SVM in Shoeprint Images Retrieval [J]. Computer Science, 2020, 47(11A): 244-247.
[4] YANG Si-yan,HE Guo-qi,LIU Ru-yi. Video Stitching Algorithm Based on SIFT and Its Optimization [J]. Computer Science, 2019, 46(7): 286-291.
[5] XING Wen-bo, DU Zhi-chun. Digital Image Forensics for Copy and Paste Tampering [J]. Computer Science, 2019, 46(6A): 380-384.
[6] SHAO Jin-da, YANG Shuai, CHENG Lin. UAV Image Matching Algorithm Based on Improved SIFT Algorithm and Two-stage Feature Matching [J]. Computer Science, 2019, 46(6): 316-321.
[7] SUN Xue-qiang, HUANG Min, ZHANG Gui-feng, ZHAO Bao-wei, CONG Lin-xiao. Multispectral Image Matching Algorithm Based on Improved SIFT [J]. Computer Science, 2019, 46(4): 280-284.
[8] LIU Zhao-xia, SHAO Feng, JING Yu and QI Rui-hua. Feature Matching Algorithm Based on Visual Feature Constrained Energy Minimization [J]. Computer Science, 2018, 45(5): 228-231.
[9] GONG An, FEI Fan and ZHENG Jun. Multi-person Behavior Recognition Method Based on Convolutional Neural Networks [J]. Computer Science, 2018, 45(2): 306-311.
[10] LOU Hao-feng, ZHANG Duan. Gaussian Process Assisted CMA-ES Application in Medical Image Registration [J]. Computer Science, 2018, 45(11A): 234-237.
[11] LI Dan, XIAO Li-qing, TIAN Jun and SUN Jin-ping. Multi-images Mosaic Algorithm Based on Improved Phase Correlation and Feature Point Registration [J]. Computer Science, 2018, 45(1): 313-319.
[12] ZHOU Shi-hao and ZHANG Yun. Log-polar Feature Guided Iterative Closest Point Algorithm [J]. Computer Science, 2018, 45(1): 297-306.
[13] ZHENG Wei, JIANG Chen-jiao, LIU Shuai-qi and ZHAO Jie. Improved Chicken Swarm Optimization Algorithm and Its Application in DTI-FA Image Registration [J]. Computer Science, 2018, 45(1): 285-291.
[14] LIU Chuan-xi, ZHAO Ru-jin, LIU En-hai and HONG Yu-zhen. Estimate Threshold of SIFT Matching Adaptively Based on RANSAC [J]. Computer Science, 2017, 44(Z6): 157-160.
[15] WANG Yi, XU Wen-di, YU Hui-bin, ZHENG He-rong and PAN Xiang. Interactive Image Co-segmentation with Saliency Constraint [J]. Computer Science, 2017, 44(Z11): 269-272.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
渝ICP备16013121号-4
Add:18# Honghu West Rd., Yubei ,Chongqing,China    Post Code: 401121
Tel: 023-63500828/023-67039612/023-67039623
E-mail: jsjkx12@163.com
Powered by Beijing Magtech Co., Ltd.