DocumentCode :
2191922
Title :
Automated interpretation of very-high resolution SAR images
Author :
Singh, Jagmal ; Datcu, Mihai
Author_Institution :
Remote Sensing Technol. Inst. (IMF), German Aerosp. Center (DLR), Oberpfaffenhofen, Germany
fYear :
2012
fDate :
22-27 July 2012
Firstpage :
3724
Lastpage :
3727
Abstract :
Very-high resolution (VHR) synthetic aperture radar (SAR) images from the last generation satellites such as TerraSAR-X and TanDEM-X exhibits special characteristics, especially in the urban-areas. Consequently, attention is needed on special considerations while developing algorithms for SAR image processing and its applications for automated interpretation. With automatic interpretation we refer to the information extraction and characterization for image categorization, retrieval, segmentation, automated target recognition etc.. In this article we focus our attention to the problem of SAR image categorization. The interest in SAR image categorization in VHR SAR (on the contrary to the pixel-based classification in low-resolution SAR images) has increased with enhanced resolution providing opportunity to carry out a more detailed analysis of targets and objects. SAR image categorization requires generation of a compact feature descriptor which accurately define the image content. A feature descriptor can be generated using `parametric´ or `non-parametric´ approaches in `image´ or `image within a transformation space´. The objective of this article is to review some selected techniques for this purpose in form of a methodological classification. Qualitative assessment of selected algorithms is presented.
Keywords :
feature extraction; geophysical image processing; image classification; image recognition; image resolution; image segmentation; radar imaging; remote sensing by radar; synthetic aperture radar; SAR image categorization; SAR image processing; TanDEM-X characteristics; TerraSAR-X characteristics; automated target recognition; image retrieval; image segmentation; low-resolution SAR images; nonparametric approaches; parametric approaches; pixel-based classification; qualitative assessment; transformation space; urban-areas; very-high resolution SAR images; very-high resolution synthetic aperture radar images; Feature extraction; Image resolution; Noise; Probability density function; Speckle; Synthetic aperture radar; Wavelet transforms; SAR image categorization; Synthetic aperture radar; feature descriptor; very-high resolution;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International
Conference_Location :
Munich
ISSN :
2153-6996
Print_ISBN :
978-1-4673-1160-1
Electronic_ISBN :
2153-6996
Type :
conf
DOI :
10.1109/IGARSS.2012.6350508
Filename :
6350508
Link To Document :
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