24.8.4.4.3 Ship Wake Detection

Chapter Contents (Back)
Ship Wake. Wakes. Often it uses SAR and Radar:
See also Radar, SAR, Ship Detection.

Rey, M.T., Tunaley, J.K., Folinsbee, J.T., Jahans, P.A., Dixon, J.A., Vent, M.R.,
Application of Random Transform Techniques to Wake Detection in Seasat-A SAR Images,
GeoRS(28), 1990, pp. 561-566. SAR. BibRef 9000

Copeland, A.C., Ravichandran, G., Trivedi, M.M.,
Radon Transform based Ship-Wake Detection,
GeoRS(33), No. 1, January 1995, pp. 35-45.
IEEE Top Reference. BibRef 9501
Earlier:
Localized Radon Transform-Based Detection of Linear Features in Noisy Images,
CVPR94(664-667).
IEEE DOI Hough Transform. SAR Image Analysis. BibRef

Magli, E., Olmo, G.,
Intelligent pattern detection and compression. An application to very low bit rate transmission of ship wake aerial images,
PRL(20), No. 2, February 1999, pp. 215-220. BibRef 9902

Kuo, J.M.[Jin Min], Chen, K.S.,
The application of wavelets correlator for ship wake detection in SAR images,
GeoRS(41), No. 6, June 2003, pp. 1506-1511.
IEEE Abstract. 0308
BibRef

Zilman, G., Zapolski, A., Marom, M.,
On Detectability of a Ship's Kelvin Wake in Simulated SAR Images of Rough Sea Surface,
GeoRS(53), No. 2, February 2015, pp. 609-619.
IEEE DOI 1411
Radon transforms BibRef

Graziano, M.D.[Maria Daniela], d'Errico, M.[Marco], Rufino, G.[Giancarlo],
Wake Component Detection in X-Band SAR Images for Ship Heading and Velocity Estimation,
RS(8), No. 6, 2016, pp. 498.
DOI Link 1608
BibRef

Fujimura, A., Soloviev, A., Rhee, S.H., Romeiser, R.,
Coupled Model Simulation of Wind Stress Effect on Far Wakes of Ships in SAR Images,
GeoRS(54), No. 5, May 2016, pp. 2543-2551.
IEEE DOI 1604
computational fluid dynamics BibRef

Graziano, M.D.[Maria Daniela], Grasso, M.[Marco], d'Errico, M.[Marco],
Performance Analysis of Ship Wake Detection on Sentinel-1 SAR Images,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712
BibRef

Sun, Y.X., Liu, P., Jin, Y.Q.,
Ship Wake Components: Isolation, Reconstruction, and Characteristics Analysis in Spectral, Spatial, and TerraSAR-X Image Domains,
GeoRS(56), No. 7, July 2018, pp. 4209-4224.
IEEE DOI 1807
Dispersion, Image reconstruction, Kelvin, Marine vehicles, Shape, Spectral analysis, Synthetic aperture radar, synthetic aperture radar (SAR) image BibRef

Tings, B.[Björn], Pleskachevsky, A.[Andrey], Velotto, D.[Domenico], Jacobsen, S.[Sven],
Extension of Ship Wake Detectability Model for Non-Linear Influences of Parameters Using Satellite Based X-Band Synthetic Aperture Radar,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Karakus, O., Rizaev, I., Achim, A.,
Ship Wake Detection in SAR Images via Sparse Regularization,
GeoRS(58), No. 3, March 2020, pp. 1665-1677.
IEEE DOI 2003
BibRef
And: Correction: GeoRS(58), No. 9, September 2020, pp. 6122-6123.
IEEE DOI 2008
Generalized minimax concave (GMC) regularization, inverse problem, maximum a posteriori (MAP) estimation, synthetic aperture radar (SAR) imagery. Sea surface, Image color analysis BibRef

Graziano, M.D.[Maria Daniela],
Preliminary Results of Ship Detection Technique by Wake Pattern Recognition in SAR Images,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Tings, B.[Björn],
Non-Linear Modeling of Detectability of Ship Wake Components in Dependency to Influencing Parameters Using Spaceborne X-Band SAR,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Xue, F.[Fuduo], Jin, W.Q.[Wei-Qi], Qiu, S.[Su], Yang, J.[Jie],
Airborne optical polarization imaging for observation of submarine Kelvin wakes on the sea surface: Imaging chain and simulation,
PandRS(178), 2021, pp. 136-154.
Elsevier DOI 2108
Polarized light imaging, Kelvin wake, Sea surface, Wave-current interaction, pBRDF, Ray tracing BibRef

Chan, Y.T.[Yi-Tung],
Maritime filtering for images and videos,
SP:IC(99), 2021, pp. 116477.
Elsevier DOI 2111
Maritime noise suppression, Maritime signal processing, Maritime foreground segmentation, Autonomous ships, Wake removal BibRef

Graziano, M.D.[Maria Daniela], Renga, A.[Alfredo],
Towards Automatic Recognition of Wakes Generated by Dark Vessels in Sentinel-1 Images,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Wang, L.[Letian], Zhang, M.[Min], Liu, J.[Jiong],
Electromagnetic Scattering Model for Far Wakes of Ship with Wind Waves on Sea Surface,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112
BibRef

del Prete, R.[Roberto], Graziano, M.D.[Maria Daniela], Renga, A.[Alfredo],
First Results on Wake Detection in SAR Images by Deep Learning,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Ding, K.Y.[Kai-Yang], Yang, J.F.[Jun-Feng], Wang, Z.[Zhao], Ni, K.[Kai], Wang, X.O.[Xia-Ohao], Zhou, Q.[Qian],
Specific Windows Search for Multi-Ship and Multi-Scale Wake Detection in SAR Images,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Ying, S.P.[Shi-Peng], Qu, H.S.[Hong-Song], Tao, S.P.[Shu-Ping], Zheng, L.L.[Liang-Liang], Wu, X.B.[Xia-Bin],
Radiation Sensitivity Analysis of Ocean Wake Information Detection System Based on Visible Light Remote Sensing,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Wang, H.[Hui], Nie, D.[Ding], Zuo, Y.[Yacong], Tang, L.[Lu], Zhang, M.[Min],
Nonlinear Ship Wake Detection in SAR Images Based on Electromagnetic Scattering Model and YOLOv5,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Grosso, E.[Elena], Guida, R.[Raffaella],
A New Automated Ship Wake Detector for Small and Go-Fast Ships in Sentinel-1 Imagery,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Tings, B.[Björn], Pleskachevsky, A.[Andrey], Wiehle, S.[Stefan],
Comparison of detectability of ship wake components between C-Band and X-Band synthetic aperture radar sensors operating under different slant ranges,
PandRS(196), 2023, pp. 306-324.
Elsevier DOI 2302
Detectability modelling, Machine learning, Maritime object detection, Ship wake detection, Synthetic aperture radar BibRef

Wang, J.J.[Jing-Jing], Guo, L.X.[Li-Xin], Wei, Y.[Yiwen], Chai, S.[Shuirong],
Study on Ship Kelvin Wake Detection in Numerically Simulated SAR Images,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Qiao, Q.Y.[Qing-Yu], Kong, X.Z.[Xiang-Zheng], Wu, S.[Shufeng], Liu, G.C.[Guo-Chang], Zhang, G.J.[Guo-Jun], Yang, H.[Hua], Zhang, W.D.[Wen-Dong], Yang, Y.H.[Yu-Hua], Jia, L.C.[Li-Cheng], He, C.[Changde], Cui, J.[Jiangong], Wang, R.[Renxin],
A Bio-Inspired MEMS Wake Detector for AUV Tracking and Coordinated Formation,
RS(15), No. 11, 2023, pp. 2949.
DOI Link 2306
BibRef

Wu, S.Y.[Shu-Ya], Wang, Y.H.[Yun-Hua], Li, Q.[Qian], Zhang, Y.M.[Yan-Min], Bai, Y.N.[Yi-Ning], Zheng, H.L.[Hong-Lei],
Simulation of Synthetic Aperture Radar Images for Ocean Ship Wakes,
RS(15), No. 23, 2023, pp. 5521.
DOI Link 2312
BibRef

Jiang, Y.[Yanni], Yang, Z.Y.[Zi-Yuan], Li, K.[Ke], Liu, T.[Tao],
Pre-Processing of Simulated Synthetic Aperture Radar Image Scenes Using Polarimetric Enhancement for Improved Ship Wake Detection,
RS(16), No. 4, 2024, pp. 658.
DOI Link 2402
BibRef


Yang, T., Karakus, O., Achim, A.,
Detection Of Ship Wakes In Sar Imagery Using Cauchy Regularisation,
ICIP20(3473-3477)
IEEE DOI 2011
Marine vehicles, Radon, Transforms, Inverse problems, Synthetic aperture radar, Image reconstruction, Cost function, Cauchy Proximal Operator BibRef

Rizaev, I., Karakus, O., Hogan, S.J., Achim, A.,
The Effect Of Sea State On Ship Wake Detectability In Simulated Sar Imagery,
ICIP20(3478-3482)
IEEE DOI 2011
Sea state, Marine vehicles, Indexes, Sea surface, Kelvin, Simulation, Satellites, SAR Imagery Simulation, Ship Wake, Wave Spectrum BibRef

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
ATR -- IR, Infra-Red, Thermal, Applications .


Last update:Mar 16, 2024 at 20:36:19