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Bathymetry Estimation From Single-Frame Images of Nearshore Waves

机译:从近岸波浪的单帧图像进行测深法估计

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Existing methods for determining bathymetry from remotely sensed images of nearshore waves exploit only information on the magnitude of wavenumber $(k = 2pi/L)$, ignoring spatial changes in wave direction $theta$ that can provide information about bathymetry gradients. These methods also require wave period information, so they can only be used when time series imagery is available. We present an algorithm where changes in direction of refracting waves are used to determine underlying bathymetry gradients based on the irrotationality of wavenumber condition. Depth dependences are explicitly introduced through the linear dispersion relationship. The final form of the model is independent of wave period so that all necessary input measurements can be derived from a single aerial snapshot taken from a plane, unmanned aerial vehicle, or satellite. Three different methods were tested for extracting wavenumber and angle from images, i.e., two based on spatial gradients of wave phase and one based on integrated travel times between sample locations (a tomographic approach). Synthetic testing using monochromatic and bichromatic waves, with and without noise, showed that while all three methods work well under ideal wave conditions, gradient methods were overly sensitive to data imperfections. The tomographic approach yielded robust wave measurements and provided confidence limits to objectively identify unusable areas. Further tests of this method using monochromatic waves on three synthetic bathymetries of increasing complexity showed a mean bathymetry bias of 0.01 m and a mean rms error of 0.17 m. While not always applicable, the model provides an alternative form of bathymetry estimation when celerity information is not available.
机译:现有的从近岸波的遥感图像确定水深的方法仅利用了波数$(k = 2pi / L)$的大小的信息,而忽略了可以提供有关水深梯度的信息的波方向$ theta的空间变化。这些方法还需要波浪周期信息,因此只能在可获得时间序列图像时使用。我们提出了一种算法,其中基于波数条件的不旋转性,使用折射波方向的变化来确定基础测深梯度。深度相关性通过线性色散关系明确引入。该模型的最终形式与波浪周期无关,因此所有必要的输入测量值都可以从飞机,无人机或卫星拍摄的单个空中快照中得出。测试了三种不同的方法从图像中提取波数和角度,即两种基于波相位的空间梯度,另一种基于样本位置之间的积分传播时间(层析成像方法)。使用带和不带噪声的单色波和双色波进行的综合测试表明,尽管这三种方法在理想的波浪条件下都能很好地工作,但梯度方法对数据缺陷过于敏感。层析成像方法产生了稳健的波测量结果,并提供了置信度限制以客观地识别不可用的区域。使用单色波对该方法进行的进一步测试在三个复杂性不断提高的合成测深仪上显示出,平均测深仪偏差为0.01 m,平均均方根误差为0.17 m。尽管并不总是适用,但当无法获得速度信息时,该模型会提供测深估算的另一种形式。

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