An Automatic Ship Detection Method Based on Local Gray-Level Gathering Characteristics in SAR Imagery
XiaoLong, Wang (Chinese Academy of Sciences. Institute of Electronics)
CuiXia, Chen (Chinese Academy of Sciences. Institute of Biophysics)

Date:	2013
Abstract:	This paper proposes an automatic ship detection method based on gray-level gathering characteristics of synthetic aperture radar (SAR) imagery. The method does not require any prior knowledge about ships and background observation. It uses a novel local gray-level gathering degree (LGGD) to characterize the spatial intensity distribution of SAR image, and then an adaptive-like LGGD thresholding and filtering scheme to detect ship targets. Experiments on real SAR images with varying sea clutter backgrounds and multiple targets situation have been conducted. The performance analysis confirms that the proposed method works well in various circumstances with high detection rate, fast detection speed and perfect shape preservation.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Local Gray-level Gathering Degree (LGGD) ; Ship Detection ; Synthetic Aperture Radar (SAR) ; Automatic Detection
Published in:	ELCVIA. Electronic letters on computer vision and image analysis, Vol. 12, Núm. 1 (2013) , p. 33-41, ISSN 1577-5097

Adreça original: https://elcvia.cvc.uab.es/article/view/v12-n1-wang-chen
Adreça alternativa: https://raco.cat/index.php/ELCVIA/article/view/280901
DOI: 10.5565/rev/elcvia.528

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