Supervised fusion-classification of multifrequency polarimetric SAR images using K distribution and theory of evidence
Importance of using multifrequency polarimetric SAR data for scene classification has been recognized in remote sensing applications. However, many problems have to be faced, due to the inadequacy of the conventional classification techniques because of the nature of the SAR images. This paper demon...
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| container_end_page | 2003 vol.4 |
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| creator | Chitroub, S. Hamiti, R. Allal, S. Houacine, A. Sansal, B. |
| description | Importance of using multifrequency polarimetric SAR data for scene classification has been recognized in remote sensing applications. However, many problems have to be faced, due to the inadequacy of the conventional classification techniques because of the nature of the SAR images. This paper demonstrates the feasibility of using the theory of evidence to merge and classify this type of image. The data are modeled using the generalized K distribution. The suggested methodology is evaluating using SAR images provided by SIR-C. |
| doi_str_mv | 10.1109/IGARSS.1999.775013 |
| format | Conference Proceeding |
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| identifier | ISBN: 0780352076 |
| ispartof | IEEE 1999 International Geoscience and Remote Sensing Symposium. IGARSS'99 (Cat. No.99CH36293), 1999, Vol.4, p.2001-2003 vol.4 |
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| language | eng |
| recordid | cdi_ieee_primary_775013 |
| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Application software Backscatter Distributed computing Image sensors Laboratories Layout Probability Remote sensing Sensor phenomena and characterization Speckle |
| title | Supervised fusion-classification of multifrequency polarimetric SAR images using K distribution and theory of evidence |
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