Efficient and accurate set-based registration of time-separated aerial images

Arandjelovic, Ognjen, Pham, Duc-Son and Venkatesh, Svetha 2015, Efficient and accurate set-based registration of time-separated aerial images, Pattern recognition, vol. 48, no. 11, pp. 3466-3476, doi: 10.1016/j.patcog.2015.04.011.

Attached Files
Name Description MIMEType Size Downloads

Title Efficient and accurate set-based registration of time-separated aerial images
Author(s) Arandjelovic, Ognjen
Pham, Duc-Son
Venkatesh, SvethaORCID iD for Venkatesh, Svetha orcid.org/0000-0001-8675-6631
Journal name Pattern recognition
Volume number 48
Issue number 11
Start page 3466
End page 3476
Total pages 11
Publisher Elsevier
Place of publication Amsterdam, The Netherlands
Publication date 2015-11
ISSN 0031-3203
Keyword(s) Alignment
Science & Technology
Computer Science, Artificial Intelligence
Engineering, Electrical & Electronic
Computer Science
Summary This paper addresses the task of time-separated aerial image registration. The ability to solve this problem accurately and reliably is important for a variety of subsequent image understanding applications. The principal challenge lies in the extent and nature of transient appearance variation that a land area can undergo, such as that caused by the change under illumination conditions, seasonal variations, or the occlusion by non-persistent objects (people, cars). Our work introduces several major novelties (i) unlike previous work on aerial image registration, we approach the problem using a set-based paradigm; (ii) we show how image space local, pair-wise constraints can be used to enforce a globally good registration using a constraints graph structure; (iii) we show how a simple holistic representation derived from raw aerial images can be used as a basic building block of the constraints graph in a manner which achieves both high registration accuracy and speed; (iv) lastly, we introduce a new and, to the best of our knowledge, the only data corpus suitable for the evaluation of set-based aerial image registration algorithms. Using this data set, we demonstrate (i) that the proposed method outperforms the state-of-the-art for pair-wise registration already, achieving greater accuracy and reliability, while at the same time reducing the computational cost of the task and (ii) that the increase in the number of available images in a set consistently reduces the average registration error, with a major difference already for a single additional image.
Language eng
DOI 10.1016/j.patcog.2015.04.011
Field of Research 080109 Pattern Recognition and Data Mining
0899 Other Information And Computing Sciences
0906 Electrical And Electronic Engineering
0801 Artificial Intelligence And Image Processing
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, Elsevier
Persistent URL http://hdl.handle.net/10536/DRO/DU:30077470

Connect to link resolver
Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved.

Version Filter Type
Citation counts: TR Web of Science Citation Count  Cited 12 times in TR Web of Science
Scopus Citation Count Cited 15 times in Scopus
Google Scholar Search Google Scholar
Access Statistics: 276 Abstract Views, 0 File Downloads  -  Detailed Statistics
Created: Fri, 09 Mar 2018, 13:08:53 EST

Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.