Sea state from ocean video with singular spectrum analysis and extended Kalman filter
A method for estimating key parameters of ocean waves (the dominant frequency and the significant wave height) from uncalibrated monoscopic video is proposed, based on temporal variation of the wave field, specifically time series of pixel intensities. The methodology tracks the principal component...
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| Veröffentlicht in: | Signal, image and video processing image and video processing, 2022-09, Vol.16 (6), p.1497-1504 |
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| container_title | Signal, image and video processing |
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| creator | Loizou, Antonis Christmas, Jacqueline |
| description | A method for estimating key parameters of ocean waves (the dominant frequency and the significant wave height) from uncalibrated monoscopic video is proposed, based on temporal variation of the wave field, specifically time series of pixel intensities. The methodology tracks the principal component of the movement of water in the video, which we propose is associated with the dominant frequency of the ocean. To accomplish this, the singular spectrum analysis algorithm and the extended Kalman filter are used. Then, the shape of an empirical spectrum is used in order to translate the dominant frequency output into a significant wave height estimation. |
| doi_str_mv | 10.1007/s11760-021-02103-0 |
| format | Article |
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| issn | 1863-1703 1863-1711 |
| language | eng |
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| subjects | Algorithms Computer Imaging Computer Science Empirical analysis Estimation Extended Kalman filter Image Processing and Computer Vision Multimedia Information Systems Original Paper Pattern Recognition and Graphics Sea states Signal,Image and Speech Processing Spectrum analysis Vision Wave height |
| title | Sea state from ocean video with singular spectrum analysis and extended Kalman filter |
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