Wave information retrieval from videos captured by a single camera has been increasingly applied in marine observation. However, when the camera observes ocean waves at low grazing angles, the accurate extraction of wave information from videos will be effected by the interference of the fine ripples on the sea surface. To solve this problem, this study develops a method for estimating peak wave periods from videos captured at low grazing angles. The method extracts the motion of the sea surface texture from the video and obtains the peak wave period via the spectral analysis. The calculation results captured from real-world videos are compared with those obtained from X-band radar inversion and tracking buoy movement, with maximum deviations of 8% and 14%, respectively. The analysis of the results shows that the peak wave period of the method has good stability. In addition, this paper uses a pinhole camera model to convert the displacement of the texture from pixel height to actual height and performs moving average filtering on the displacement of the texture, thus conducting a preliminary exploration of the inversion of significant wave height. This study helps to extend the application of sea surface videos.
Figure 1. Sea surface image captured by the video system. The yellow arrow in the figure points to the direction of wave propagation, and the white box indicates the sampling region used to identify the waves.
Figure 2. Sub-images of six moments taken from the video. The textures in the image show upward (a, b, c) and downward (d, e, f) movement as the waves pass by.
Figure 3. Flow diagram of video analysis.
Figure 4. Schematic of sub-image matching (left) and matching results (right). Lighter grey scale indicates larger values; the black box in the figure indicates the position of the maximum value obtained from the matching process; the red dashed box denotes the center of the image
Figure 5. Texture displacements were derived by matching between every two adjacent frames before and after the wave passes the observation position (upper curve), and continuous texture displacements were obtained by accumulating the displacement data (lower curve).
Figure 6. Frame from the video showing three selected regions (A, B, and C) for wave parameter extraction.
Figure 7. Texture displacement in Region A.
Figure 8. Spectrum of texture displacement in Region A.
Figure 9. Wave spectra calculated from buoy motion data.
Figure 10. Selected region for assessing the impact of distance.
Figure 11. Spectrum derived from texture displacement extracted at a distant location.
Figure 12. Relationship between height in the image and real-world height.
Figure 13. Sea surface elevation after filtering.
Figure 14. Wave spectrum plotted from filtered sea surface elevation.
Figure 15. Comparison of texture displacement between 10 pixel × 10 pixel and 20 pixel × 20 pixel.
Figure 16. The simulated sea surface video image.
Figure 17. Comparison between the peak wave periods calculated from the sub-image sizes ranging from 10 pixel × 10 pixel to 100 pixel × 100 pixel and the theoretical values, under wind speed conditions of 3 m/s, 7 m/s, and 12 m/s.
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