Segmentation of oil spills in SAR images by using discriminant cuts

Autor:	Xianwen Ding, Xiaolin Zou
Rok vydání:	2018
Předmět:	Synthetic aperture radar Computer science business.industry fungi Pattern recognition Image segmentation Fuzzy logic body regions Discriminant Oil spill Classification methods Segmentation Artificial intelligence skin and connective tissue diseases business Spatial analysis
Zdroj:	MIPPR 2017: Automatic Target Recognition and Navigation.
DOI:	10.1117/12.2287314
Popis:	The discriminant cut is used to segment the oil spills in synthetic aperture radar (SAR) images. The proposed approach is a region-based one, which is able to capture and utilize spatial information in SAR images. The real SAR images, i.e. ALOS-1 PALSAR and Sentinel-1 SAR images were collected and used to validate the accuracy of the proposed approach for oil spill segmentation in SAR images. The accuracy of the proposed approach is higher than that of the fuzzy C-means classification method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::65b2f7065bde9c3f4c78a725f41425ea https://doi.org/10.1117/12.2287314 Zobrazit plný text záznamu