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首页> 外文期刊>Annals of Glaciology >Tracking the motion of recognizable sea-ice objects from coastal radar image sequences
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Tracking the motion of recognizable sea-ice objects from coastal radar image sequences

机译:从沿海雷达图像序列跟踪可识别的海冰物体的运动

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The Finnish Meteorological Institute has installed image-capturing devices on some Baltic Sea coastal radars for operational sea-ice monitoring and ice product validation. These devices produce radar images, which are saved operationally at about every 2min. These data can efficiently be utilized in automated tracking of ice motion over sequences of radar images. Reliable estimates of point-wise ice drift can be used as virtual drifter buoys to validate fine-scale ice models. For this purpose we have developed an algorithm, which first locates objects that can reliably be recognized from one radar image to another, and then tracks the motion of these objects until they are lost by the algorithm. The recognizable objects in the first image of an image sequence are located by requiring an object to include a textural content, i.e. the object does not solely consist of a uniform area, and detected edge corner points. The corner points are required to exclude straight linear edges. After locating a suitable number of traceable objects, the tracking is performed between each pair of successive images using a two-resolution phase-correlation algorithm. We have tested the tracking algorithm using image sequences of two coastal radars collected during the 2010/11 and 2011/12 winters.
机译:芬兰气象研究所已在一些波罗的海沿岸雷达上安装了图像捕获设备,用于运行中的海冰监测和冰产品验证。这些设备会产生雷达图像,大约每2分钟可操作保存一次。这些数据可以有效地用于在雷达图像序列上自动跟踪冰运动。逐点冰漂的可靠估计可以用作虚拟漂流浮标,以验证小规模的冰模型。为此,我们开发了一种算法,该算法首先将可以从一个雷达图像可靠地识别到另一个图像的对象定位,然后跟踪这些对象的运动,直到它们被算法丢失。通过要求对象包括纹理内容来定位图像序列的第一图像中的可识别对象,即,该对象不仅由均匀区域和检测到的边缘拐角点组成。需要拐角点以排除直线直线边缘。在找到合适数量的可跟踪对象之后,使用双分辨率相位相关算法在每对连续图像之间执行跟踪。我们已经使用2010/11和2011/12冬季收集的两个沿海雷达的图像序列测试了跟踪算法。

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