Oil spill detection: SAR multi-scale segmentation & object features evaluation

Topouzelis, K; Karathanassi, V; Pavlakis, P; Rokos, D

dc.contributor.author	Topouzelis, K	en
dc.contributor.author	Karathanassi, V	en
dc.contributor.author	Pavlakis, P	en
dc.contributor.author	Rokos, D	en
dc.date.accessioned	2014-03-01T02:49:15Z
dc.date.available	2014-03-01T02:49:15Z
dc.date.issued	2002	en
dc.identifier.issn	0277786X	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/34442
dc.subject	Hierarchical classification network	en
dc.subject	Knowledge base	en
dc.subject	Multi-scale segmentation	en
dc.subject	Object image analysis	en
dc.subject	Oil spills	en
dc.subject	SAR	en
dc.subject.other	Feature extraction	en
dc.subject.other	Fuzzy sets	en
dc.subject.other	Image analysis	en
dc.subject.other	Image segmentation	en
dc.subject.other	Marine pollution	en
dc.subject.other	Oil spills	en
dc.subject.other	Radar imaging	en
dc.subject.other	Synthetic aperture radar	en
dc.subject.other	Multi scale segmentation	en
dc.subject.other	Object feature extraction	en
dc.subject.other	Remote sensing	en
dc.title	Oil spill detection: SAR multi-scale segmentation & object features evaluation	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1117/12.462518	en
heal.identifier.secondary	http://dx.doi.org/10.1117/12.462518	en
heal.publicationDate	2002	en
heal.abstract	The use of image segmentation and object feature extraction in order to classify SAR image objects into oil spill or other features (oil slick look-alikes), it is widely acceptable in oil spill detection research. For this purpose, a number of features (geometric, surrounding, backscattering, etc.) are usually calculated and introduced in a decision support procedure. The aim of the present study is presentation, analysis and evaluation of the above features in order to produce general rules adequate to identify oil spills in any SAR image. SAR image processing is based on a new multi-segmentation technique. As a first step, image objects in different scales are extracted using the multi-segmentation procedure. Following segmentation, a hierarchical network of image objects is developed, which simultaneously presents object information and fuzzy rules for classification. In experiments implemented in SAR images, the method developed has successfully detected oil spills and look alikes. Texture behavior most contributes to detection (texture characteristics 80%), followed by physical behavior (actual backscatter characteristics 53%, spot surroundings 26%) and finally geometry behavior (geometrical characteristics 2%).	en
heal.journalName	Proceedings of SPIE - The International Society for Optical Engineering	en
dc.identifier.doi	10.1117/12.462518	en
dc.identifier.volume	4880	en
dc.identifier.spage	77	en
dc.identifier.epage	87	en