NDLI: Automatic detection of oil spills in ENVISAT, Radarsat and ERS SAR images

Content Provider	IEEE Xplore Digital Library
Author	Solberg, A.H.S. Dokken, S.T. Solberg, R.
Copyright Year	2003
Description	Author affiliation: Dept. of Stat. Anal., Image Anal. & Pattern Recognition, Norwegian Comput. Center, Oslo, Norway (Solberg, A.H.S.; Dokken, S.T.; Solberg, R.)
Abstract	We present a framework for automatic detection of oil spills in SAR images. Multi incident angle and multi polarization SAR data are ingested into the framework in order to optimize revisit times and thereby the temporal and spatial coverage. Dark spots in the images are primarily detected by adaptive thresholding. For each of them a number of features are computed in order to classify the slick as either an oil slick or a 'look-alike' (other oceanographic phenomena which resemble oil slicks). A classification scheme is utilized based on statistical modeling. A data set of about 100 images from each of the sensors ERS, Radarsat and ENVISAT is or will soon be available to train and test the algorithm. In this paper, only results from ERS and Radarsat are reported because the access of ENVISAT images has been delayed.
Starting Page	2747
Ending Page	2749
File Size	1911344
Page Count	3
File Format	PDF
ISBN	0780379292
DOI	10.1109/IGARSS.2003.1294572
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-07-21
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Petroleum Wind Image analysis Statistical analysis Pattern recognition Inspection Backscatter Shape Humans Detection algorithms
Content Type	Text
Resource Type	Article

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