Paper Info
Title
Building Change Detection using Coherent and Incoherent Features from Multitemporal SAR Images
Abstract
In this paper, we propose a novel method for building change detection using coherent and incoherent features of high resolution multi-temporal synthetic aperture radar (SAR) images. Three coherent and incoherent features are used to define pixel-level building change, while initial result is obtained through multi-threshold. After that, initial result is segmented into different areas based on the same time of change. Then, dynamic time warping (DTW) similarity measure is selected for binary classification in each area to separate it into changed and unchanged classes. Experimental result obtained from 10 TerraSAR-X Stripmap SAR images, shows the effective performance of the proposed approach.
Year
DOI
Venue
2019
10.1109/Multi-Temp.2019.8866968
2019 10th International Workshop on the Analysis of Multitemporal Remote Sensing Images (MultiTemp)
Keywords
Field
DocType
SAR,building changed detection,DTW similarity measure,classification
Time series,Change detection,Similarity measure,Binary classification,Dynamic time warping,Pattern recognition,Synthetic aperture radar,Computer science,Coherence (physics),Artificial intelligence
Conference
ISBN
Citations 
PageRank 
978-1-7281-4616-4
0
0.34
References 
Authors
7
3
Name
Order
Citations
PageRank
Hao Feng140932.15
Lu Zhang23510.89
Mingsheng Liao319143.90