A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM

Remote sensing system fitted on UAV (Unmanned Aerial Vehicle) can obtain clear images and high-resolution aerial photographs. It has advantages of flexibility, convenience and ability to work full-time. However, there are some problems of UAV image such as small coverage area, large number, irregula...

Full description

Bibliographic Details
Main Authors: T. J. Lei, R. R. Xu, J. H. Cheng, W. L. Song, W. Jiang, W. Qu, J. X. Lu, S. Li
Format: Article
Language:English
Published: Copernicus Publications 2020-08-01
Series:The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Online Access:https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B1-2020/471/2020/isprs-archives-XLIII-B1-2020-471-2020.pdf
_version_ 1819142946083045376
author T. J. Lei
R. R. Xu
R. R. Xu
J. H. Cheng
J. H. Cheng
W. L. Song
W. Jiang
W. Qu
J. X. Lu
S. Li
author_facet T. J. Lei
R. R. Xu
R. R. Xu
J. H. Cheng
J. H. Cheng
W. L. Song
W. Jiang
W. Qu
J. X. Lu
S. Li
author_sort T. J. Lei
collection DOAJ
description Remote sensing system fitted on UAV (Unmanned Aerial Vehicle) can obtain clear images and high-resolution aerial photographs. It has advantages of flexibility, convenience and ability to work full-time. However, there are some problems of UAV image such as small coverage area, large number, irregular overlap, etc. How to obtain a large regional map quickly becomes a major obstacle to UAV remote sensing application. In this paper, a new method of fast registration of UAV remote sensing images was proposed to meet the needs of practical application. This paper used Progressive Sample Consensus (PROSAC) algorithm to improve the matching accuracy by removed a large number of mismatching point pairs of remote sensing image registration based-on SURF (Speed Up Robust Feature) algorithm, and GPU (Graphic Processing Unit) was also used to accelerate the speed of improved SURF algorithm. Finally, geometric verification was used to achieve mosaic accuracy in survey area. The number of feature points obtained by using improved SURF based-on PROSAC algorithm was only 9.5% than that of SURF algorithm. Moreover, the accuracy rate of improved method was about 99.7%, while the accuracy rate of improved SURF algorithm was increased by 8% than SURF algorithm. Moreover, the improved running time of SURFGPU algorithm for UAV remote sensing image registration was a speed of around 16 times than SURF algorithm, and the image matching time had reached millisecond level. Thus, improved SURF algorithm had better matching accuracy and executing speed to meet the requirements of real-time and robustness in UAV remote sensing image registration.
first_indexed 2024-12-22T12:18:25Z
format Article
id doaj.art-c568a50122214f3180630cb93804c05c
institution Directory Open Access Journal
issn 1682-1750
2194-9034
language English
last_indexed 2024-12-22T12:18:25Z
publishDate 2020-08-01
publisher Copernicus Publications
record_format Article
series The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
spelling doaj.art-c568a50122214f3180630cb93804c05c2022-12-21T18:26:04ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342020-08-01XLIII-B1-202047147810.5194/isprs-archives-XLIII-B1-2020-471-2020A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHMT. J. Lei0R. R. Xu1R. R. Xu2J. H. Cheng3J. H. Cheng4W. L. Song5W. Jiang6W. Qu7J. X. Lu8S. Li9China Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaChina Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, ChinaChina Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaSchool of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454000, ChinaChina Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaChina Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaChina Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaChina Institute of Water Resources and Hydropower Research (IWHR), Beijing 100038, ChinaState-Province Joint Engineering Laboratory of Spatial Information Technology for High-Speed Railway Safety, Southwest Jiaotong University, Chengdu 611756, ChinaRemote sensing system fitted on UAV (Unmanned Aerial Vehicle) can obtain clear images and high-resolution aerial photographs. It has advantages of flexibility, convenience and ability to work full-time. However, there are some problems of UAV image such as small coverage area, large number, irregular overlap, etc. How to obtain a large regional map quickly becomes a major obstacle to UAV remote sensing application. In this paper, a new method of fast registration of UAV remote sensing images was proposed to meet the needs of practical application. This paper used Progressive Sample Consensus (PROSAC) algorithm to improve the matching accuracy by removed a large number of mismatching point pairs of remote sensing image registration based-on SURF (Speed Up Robust Feature) algorithm, and GPU (Graphic Processing Unit) was also used to accelerate the speed of improved SURF algorithm. Finally, geometric verification was used to achieve mosaic accuracy in survey area. The number of feature points obtained by using improved SURF based-on PROSAC algorithm was only 9.5% than that of SURF algorithm. Moreover, the accuracy rate of improved method was about 99.7%, while the accuracy rate of improved SURF algorithm was increased by 8% than SURF algorithm. Moreover, the improved running time of SURFGPU algorithm for UAV remote sensing image registration was a speed of around 16 times than SURF algorithm, and the image matching time had reached millisecond level. Thus, improved SURF algorithm had better matching accuracy and executing speed to meet the requirements of real-time and robustness in UAV remote sensing image registration.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B1-2020/471/2020/isprs-archives-XLIII-B1-2020-471-2020.pdf
spellingShingle T. J. Lei
R. R. Xu
R. R. Xu
J. H. Cheng
J. H. Cheng
W. L. Song
W. Jiang
W. Qu
J. X. Lu
S. Li
A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
title A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM
title_full A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM
title_fullStr A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM
title_full_unstemmed A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM
title_short A NEW METHOD OF FAST REGISTRATION OF UNMANNED AERIAL VEHICLE REMOTE SENSING IMAGES BASED-ON AN IMPROVED SURF ALGORITHM
title_sort new method of fast registration of unmanned aerial vehicle remote sensing images based on an improved surf algorithm
url https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLIII-B1-2020/471/2020/isprs-archives-XLIII-B1-2020-471-2020.pdf
work_keys_str_mv AT tjlei anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT rrxu anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT rrxu anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT jhcheng anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT jhcheng anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT wlsong anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT wjiang anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT wqu anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT jxlu anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT sli anewmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT tjlei newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT rrxu newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT rrxu newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT jhcheng newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT jhcheng newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT wlsong newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT wjiang newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT wqu newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT jxlu newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm
AT sli newmethodoffastregistrationofunmannedaerialvehicleremotesensingimagesbasedonanimprovedsurfalgorithm