Application Of Radon Transform Techniques To Wake Detection In Seasat-A SAR Images

Rey, María Teresa de Tena; Tunaley, J. K. E.; Folinsbee, J.T.; Jahans, P.A.; Dixon, J.A.; Vant, M.R.

doi:10.1109/tgrs.1990.572948

Cited by 155 publications

(51 citation statements)

References 5 publications

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“…Ship wake has been largely exploited for ship route estimation by high resolution Synthetic Aperture Radar (SAR) images, and several techniques have been proposed to improve wake detection [1][2][3][4][5][6][7][8] and velocity estimation performance [3,4]. The common assumption of the existing approaches is related to wake structure, which is basically composed by the turbulent wake, two narrow-V wakes, and the Kelvin pattern [9].…”

Section: Introductionmentioning

confidence: 99%

“…The technique takes advantages from the Radon-based previous techniques [1,3], but it has been conceived to overcome their intrinsic limitations by exploiting the relative angular distance of wake components during the detection process. In detail, the detection phase leads to the identification of five wake components, which are then classified as really imaged or not by means of merit indexes.…”

Section: Introductionmentioning

confidence: 99%

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Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images

2017

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Abstract:A novel technique for ship wake detection has been recently proposed and applied on X-band Synthetic Aperture Radar images provided by COSMO/SkyMed and TerraSAR-X. The approach shows that the vast majority of wake features are correctly detected and validated in critical situations. In this paper, the algorithm was applied to 28 wakes imaged by Sentinel-1 mission with different polarizations and incidence angles with the aim of testing the method's robustness with reference to radar frequency and resolution. The detection process is properly modified. The results show that the features were correctly classified in 78.5% of cases, whereas false confirmations occur mainly on Kelvin cusps. Finally, the results were compared with the algorithm performance on X-band images, showing that no significant difference arises. In fact, the total false confirmations rate was 15.8% on X-band images and 18.5% on C-band images. Moreover, since the main criticality concerns again the false confirmation of Kelvin cusps, the same empirical criterion suggested for the X-band SAR images yielded a negligible 1.5% of false detection rate.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images

2017

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“…Such bright returns have to be removed. Differently from Rey et al [23], who propose to detect ship bright returns by setting a threshold value and to replace them with the mean value of the amplitude distribution, hereinafter, the tile is masked with a rectangular area comprised between [´δr max , δr max ] (range) and [´δa max , δa max ] (azimuth), where δr max is 1.5-times the length of the ship cluster projected onto the range direction and δa max is the maximum expected azimuth shift, computed from Equation (1) [12].…”

Section: Wake Component Detectionmentioning

confidence: 83%

Section: Wake Component Detectionmentioning

confidence: 99%

Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation

2016

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Abstract: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.

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“…Ship wakes are sometimes easier to recognize than the ship in a large ocean image. Reasons for detecting ship wakes can be found in Rey et al [23]. In short, ship wakes usually appear as a thick connected line with possible interruptions by the image noise, which is very strong in ocean SAR imagery.…”

Section: Discussionmentioning

confidence: 99%