DocumentCode
1898993
Title
Analysis of SST images by weighted Ensemble Transform Kalman Filter
Author
Gorthi, Sai Subrahmanyam ; Beyou, Sébastien ; Mémin, Étienne
Author_Institution
INRIA Rennes Bretagne-Atlantique, Rennes, France
fYear
2011
fDate
24-29 July 2011
Firstpage
4172
Lastpage
4175
Abstract
This paper presents a novel, efficient scheme for the analysis of Sea Surface Temperature (SST) ocean images. We consider the estimation of the velocity fields and vorticity values from a sequence of oceanic images. The contribution of this paper lies in proposing a novel, robust and simple approach based on Weighted Ensemble Transform Kalman filter (WETKF) data assimilation technique for the analysis of real SST images, that may contain coast regions or large areas of missing data due to the cloud cover.
Keywords
Kalman filters; geophysical image processing; image sequences; ocean temperature; oceanographic techniques; vortices; SST image; cloud cover; coast region; ocean images; sea surface temperature; velocity field; vorticity value; weighted ensemble transform Kalman filter; Data assimilation; Kalman filters; Mathematical model; Oceans; Sea measurements; Transforms; Uncertainty; Data assimilation; Ensemble Kalman filters; Image motion analysis; Particle filters;
fLanguage
English
Publisher
ieee
Conference_Titel
Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International
Conference_Location
Vancouver, BC
ISSN
2153-6996
Print_ISBN
978-1-4577-1003-2
Type
conf
DOI
10.1109/IGARSS.2011.6050049
Filename
6050049
Link To Document