DocumentCode :
144230
Title :
On the statistical similarity of synthetic aperture radar images from COSMO-SKYMED and TerraSAR-X
Author :
Singh, Jagmal ; Espinoza-Molina, Daniela ; Schwarz, Gottfried ; Datcu, Mihai
Author_Institution :
Remote Sensing Technol. Inst., German Aerosp. Center (DLR), Oberpfaffenhofen, Germany
fYear :
2014
fDate :
13-18 July 2014
Firstpage :
4726
Lastpage :
4729
Abstract :
The latest generation of synthetic aperture radar (SAR) instruments operating in X-band, that is, COSMO-SkyMed (CSK) and TerraSAR-X (TSX), are capable of providing images from coarse resolution to very high resolution. A lot of research effort has been invested in the study and understanding of images obtained from these satellites. However, there is still a huge scope of statistical understanding and comparison of data from both satellites. In this study, we demonstrate some striking similarities between medium resolution data obtained from CSK and TSX Stripmap mode images. Landcover unsupervised clustering using k-means is discussed to further justify our findings. Clustering is carried out using a feature descriptor based on log-cumulants of Gabor coefficients, which was recently proposed by us in earlier studies.
Keywords :
geophysical image processing; image resolution; land cover; pattern clustering; radar imaging; remote sensing by radar; synthetic aperture radar; COSMO-SkyMed; CSK Stripmap mode images; Gabor coefficients; TSX Stripmap mode images; TerraSAR-X; coarse resolution; feature descriptor; land-cover unsupervised clustering; log-cumulants; medium resolution data; synthetic aperture radar images; Bridges; Histograms; Image resolution; Satellites; Synthetic aperture radar; Urban areas; COSMO-SkyMed (CSK); Synthetic aperture radar (SAR); TerraSAR-X (TSX); clustering; log-cumulants;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
Type :
conf
DOI :
10.1109/IGARSS.2014.6947549
Filename :
6947549
Link To Document :
بازگشت