A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection
Successful change detection in multi-temporal images relies on high spatial co-registration accuracy. However, co-registration accuracy alone cannot meet the needs of change detection when using several ground control points to separately geo-reference multi-temporal images from unmanned aerial vehi...
Main Authors: | , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017-06-01
|
Series: | Remote Sensing |
Subjects: | |
Online Access: | http://www.mdpi.com/2072-4292/9/6/625 |
id |
doaj-3b6ac632e03644a8ba78ae3e7fd1ccf0 |
---|---|
record_format |
Article |
spelling |
doaj-3b6ac632e03644a8ba78ae3e7fd1ccf02020-11-24T23:24:28ZengMDPI AGRemote Sensing2072-42922017-06-019662510.3390/rs9060625rs9060625A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change DetectionWenzhuo Li0Kaimin Sun1Deren Li2Ting Bai3Haigang Sui4School of Remote Sensing and Information Engineering, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaState Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, 129 Luoyu Road, Wuhan 430079, ChinaSuccessful change detection in multi-temporal images relies on high spatial co-registration accuracy. However, co-registration accuracy alone cannot meet the needs of change detection when using several ground control points to separately geo-reference multi-temporal images from unmanned aerial vehicles (UAVs). This letter reports on a new approach to perform bundle adjustment—named united bundle adjustment (UBA)—to solve this co-registration problem for change detection in multi-temporal UAV images. In UBA, multi-temporal UAV images are matched with each other to construct a unified tie point net. One single bundle adjustment process is performed on the unified tie point net, placing every image into the same coordinate system and thus automatically accomplishing spatial co-registration. We then perform change detection using both orthophotos and three-dimensional height information derived from dense image matching techniques. Experimental results show that UBA co-registration accuracy is higher than the accuracy of commonly-used approaches for multi-temporal UAV images. Our proposed preprocessing method extends the capacities of consumer-level UAVs so they can eventually meet the growing need for automatic building change detection and dynamic monitoring using only RGB band images.http://www.mdpi.com/2072-4292/9/6/625united bundle adjustment (UBA)UAV imagesthree dimensionchange detection |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Wenzhuo Li Kaimin Sun Deren Li Ting Bai Haigang Sui |
spellingShingle |
Wenzhuo Li Kaimin Sun Deren Li Ting Bai Haigang Sui A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection Remote Sensing united bundle adjustment (UBA) UAV images three dimension change detection |
author_facet |
Wenzhuo Li Kaimin Sun Deren Li Ting Bai Haigang Sui |
author_sort |
Wenzhuo Li |
title |
A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection |
title_short |
A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection |
title_full |
A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection |
title_fullStr |
A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection |
title_full_unstemmed |
A New Approach to Performing Bundle Adjustment for Time Series UAV Images 3D Building Change Detection |
title_sort |
new approach to performing bundle adjustment for time series uav images 3d building change detection |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2017-06-01 |
description |
Successful change detection in multi-temporal images relies on high spatial co-registration accuracy. However, co-registration accuracy alone cannot meet the needs of change detection when using several ground control points to separately geo-reference multi-temporal images from unmanned aerial vehicles (UAVs). This letter reports on a new approach to perform bundle adjustment—named united bundle adjustment (UBA)—to solve this co-registration problem for change detection in multi-temporal UAV images. In UBA, multi-temporal UAV images are matched with each other to construct a unified tie point net. One single bundle adjustment process is performed on the unified tie point net, placing every image into the same coordinate system and thus automatically accomplishing spatial co-registration. We then perform change detection using both orthophotos and three-dimensional height information derived from dense image matching techniques. Experimental results show that UBA co-registration accuracy is higher than the accuracy of commonly-used approaches for multi-temporal UAV images. Our proposed preprocessing method extends the capacities of consumer-level UAVs so they can eventually meet the growing need for automatic building change detection and dynamic monitoring using only RGB band images. |
topic |
united bundle adjustment (UBA) UAV images three dimension change detection |
url |
http://www.mdpi.com/2072-4292/9/6/625 |
work_keys_str_mv |
AT wenzhuoli anewapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT kaiminsun anewapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT derenli anewapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT tingbai anewapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT haigangsui anewapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT wenzhuoli newapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT kaiminsun newapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT derenli newapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT tingbai newapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection AT haigangsui newapproachtoperformingbundleadjustmentfortimeseriesuavimages3dbuildingchangedetection |
_version_ |
1725560518035374080 |