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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing. >A Generalized Distance Transform: Theory and Applications to Weather Analysis and Forecasting
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A Generalized Distance Transform: Theory and Applications to Weather Analysis and Forecasting

机译：广义距离变换：天气分析和预报的理论与应用

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摘要

The distance transform (DT) (also known as distance map or distance field) is a fundamental tool of mathematical morphology. We introduce a generalized DT (GDT) that is smoother than the classical DT. This transform can be used to define a generalized Hausdorff metric that is shown to be more robust to noise while preserving all metric properties. It is also shown to lead to smoother level sets, allowing contour evolution without having to solve a partial differential equation. Two applications in weather analysis and forecasting demonstrate the usefulness of this proposed GDT. In particular, the dilation of sets according to the GDT allows the simplification of numerical weather forecasts and analysis into geometric objects, called MetObjects, and the generalized Hausdorff distance can be used as a forecast verification metric.
机译：距离变换（DT）（也称为距离图或距离场）是数学形态学的基本工具。我们介绍了比传统DT更平滑的广义DT（GDT）。此变换可用于定义广义的Hausdorff度量，该度量在保留所有度量属性的同时显示出对噪声更强的鲁棒性。它也显示出导致更平滑的水平集，从而允许轮廓演化而无需求解偏微分方程。天气分析和预报中的两个应用程序证明了此建议的GDT的有用性。特别是，根据GDT进行集合的扩展可以简化数值天气预报并将分析简化为称为MetObjects的几何对象，并且广义的Hausdorff距离可以用作预测验证指标。

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