Comparison of optimised processors for the detection and segmentation of oil slicks with polarimetric SAR images

Author

Lombardo, P. ; Conte, D.I. ; Morelli, A.

Author_Institution

Dept. INFOCOM, Rome Univ., Italy

Volume

7

fYear

2000

fDate

2000

Firstpage

2963

Abstract

Three algorithms are proposed for the CFAR detection of dark regions in polarimetric SAR images of the sea. To set the detection threshold, a closed form expression is derived for the probability of false alarm (P_fa) of the techniques that are also compared by Monte Carlo simulations. The application to a SIR-C image is also used to assess their performance

Keywords

environmental science computing; geophysical signal processing; image segmentation; oceanographic techniques; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; water pollution measurement; CFAR detection; Monte Carlo simulation; SAR polarimetry; SIR-C; algorithm; closed form expression; constant false alarm rate; dark region; detection threshold; false alarm; image segmentation; marine pollution; measurement technique; ocean; oil pollution; oil slick; optimised processor; polarimetric SAR; probability; radar imaging; radar polarimetry; radar remote sensing; synthetic aperture radar; water pollution; Covariance matrix; Detectors; Image segmentation; Maximum likelihood detection; Maximum likelihood estimation; Performance analysis; Petroleum; Sea measurements; Sea surface; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-6359-0

Type

conf

DOI

10.1109/IGARSS.2000.860303

Filename

860303