Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation
A new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estima...
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2016-06-01
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Online Access: | http://www.mdpi.com/2072-4292/8/6/498 |
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doaj-3f808c463bf84ab58e4484690e3e23762020-11-24T22:03:03ZengMDPI AGRemote Sensing2072-42922016-06-018649810.3390/rs8060498rs8060498Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity EstimationMaria Daniela Graziano0Marco D’Errico1Giancarlo Rufino2Department of Industrial Engineering, University of Naples “Federico II”, Piazzale Tecchio, 80, 80125 Naples, ItalyDepartment of Industrial and Information Engineering, Second University of Naples, via Roma, 29, 81031 Aversa, ItalyDepartment of Industrial Engineering, University of Naples “Federico II”, Piazzale Tecchio, 80, 80125 Naples, ItalyA new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estimated by state-of-the-art techniques of azimuth shift and Kelvin arm wavelength. The algorithm is applied to 13 X-band SAR images from the TerraSAR-X and COSMO/SkyMed missions with different polarization and incidence angles. Results show that the vast majority of wake features are correctly detected and validated also in critical situations, i.e., when multiple wake appearances or dark areas not related to wake features are imaged. The ship route estimations are validated with truth-at-sea in seven cases. Finally, it is also verified that the algorithm does not detect wakes in the surroundings of 10 ships without wake appearances.http://www.mdpi.com/2072-4292/8/6/498wake detectionRadon transformship velocityship heading |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Maria Daniela Graziano Marco D’Errico Giancarlo Rufino |
spellingShingle |
Maria Daniela Graziano Marco D’Errico Giancarlo Rufino Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation Remote Sensing wake detection Radon transform ship velocity ship heading |
author_facet |
Maria Daniela Graziano Marco D’Errico Giancarlo Rufino |
author_sort |
Maria Daniela Graziano |
title |
Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation |
title_short |
Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation |
title_full |
Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation |
title_fullStr |
Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation |
title_full_unstemmed |
Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation |
title_sort |
wake component detection in x-band sar images for ship heading and velocity estimation |
publisher |
MDPI AG |
series |
Remote Sensing |
issn |
2072-4292 |
publishDate |
2016-06-01 |
description |
A new algorithm for ship wake detection is developed with the aim of ship heading and velocity estimation. It exploits the Radon transform and utilizes merit indexes in the intensity domain to validate the detected linear features as real components of the ship wake. Finally, ship velocity is estimated by state-of-the-art techniques of azimuth shift and Kelvin arm wavelength. The algorithm is applied to 13 X-band SAR images from the TerraSAR-X and COSMO/SkyMed missions with different polarization and incidence angles. Results show that the vast majority of wake features are correctly detected and validated also in critical situations, i.e., when multiple wake appearances or dark areas not related to wake features are imaged. The ship route estimations are validated with truth-at-sea in seven cases. Finally, it is also verified that the algorithm does not detect wakes in the surroundings of 10 ships without wake appearances. |
topic |
wake detection Radon transform ship velocity ship heading |
url |
http://www.mdpi.com/2072-4292/8/6/498 |
work_keys_str_mv |
AT mariadanielagraziano wakecomponentdetectioninxbandsarimagesforshipheadingandvelocityestimation AT marcoderrico wakecomponentdetectioninxbandsarimagesforshipheadingandvelocityestimation AT giancarlorufino wakecomponentdetectioninxbandsarimagesforshipheadingandvelocityestimation |
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1725833490359910400 |