Next Article in Journal
Geographic Object-Based Image Analysis Framework for Mapping Vegetation Physiognomic Types at Fine Scales in Neotropical Savannas
Next Article in Special Issue
Wishart-Based Adaptive Temporal Filtering of Polarimetric SAR Imagery
Previous Article in Journal
Improving Estimation of Soil Moisture Content Using a Modified Soil Thermal Inertia Model
Open AccessFeature PaperArticle

Detecting Ephemeral Objects in SAR Time-Series Using Frozen Background-Based Change Detection

SONDRA, CentraleSupélec, Université Paris-Saclay, 3 Rue Joliot Curie, 91190 Gif-sur-Yvette, France
*
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(11), 1720; https://doi.org/10.3390/rs12111720
Received: 24 April 2020 / Revised: 15 May 2020 / Accepted: 21 May 2020 / Published: 27 May 2020
Change detection (CD) in SAR (Synthethic Aperture Radar) images has been widely studied in recent years and has become increasingly attractive due to the growth of available datasets. The potential of CD has been shown in different fields, including disaster monitoring and military applications. Access to multi-temporal SAR images of the same scene is now possible, and therefore we can improve the performance and the interpretation of CD. Apart from specific SAR campaign measurements, the ground truth of the scene is usually unknown or only partially known when dealing with open data. This is a critical issue when the purpose is to detect targets, such as vehicles or ships. Indeed, typical change detection methods can only provide relative changes; the actual number of targets on each day cannot be determined. Ideally, this change detection should occur between a target-free image and one with the objects of interest. To do so, we propose to benefit from pixels’ intrinsic temporal behavior to compute a frozen background reference (FBR) image and perform change detection from this reference image. We will then consider that the scene consists only of immobile objects (e.g., buildings and trees) and removable objects that can appear and disappear from acquisition to another (e.g., cars and ships). Our FBR images will, therefore, aim to estimate the immobile background of the scene to obtain, after change detection, the exact amount of targets present on each day. This study was conducted first with simulated SAR data for different number of acquisition dates and Signal-to-Noise Ratio (SNR). We presented an application in the region of Singapore to estimate the number of ships in the study area for each acquisition. View Full-Text
Keywords: change detection; time-series; SAR; target detection change detection; time-series; SAR; target detection
Show Figures

Graphical abstract

MDPI and ACS Style

Taillade, T.; Thirion-Lefevre, L.; Guinvarc’h, R. Detecting Ephemeral Objects in SAR Time-Series Using Frozen Background-Based Change Detection. Remote Sens. 2020, 12, 1720. https://doi.org/10.3390/rs12111720

AMA Style

Taillade T, Thirion-Lefevre L, Guinvarc’h R. Detecting Ephemeral Objects in SAR Time-Series Using Frozen Background-Based Change Detection. Remote Sensing. 2020; 12(11):1720. https://doi.org/10.3390/rs12111720

Chicago/Turabian Style

Taillade, Thibault; Thirion-Lefevre, Laetitia; Guinvarc’h, Régis. 2020. "Detecting Ephemeral Objects in SAR Time-Series Using Frozen Background-Based Change Detection" Remote Sens. 12, no. 11: 1720. https://doi.org/10.3390/rs12111720

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Search more from Scilit
 
Search
Back to TopTop