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A NOVEL NOISE REMOVAL ALGORITHM FOR VERTICAL ARTIFACTS IN DIGITAL ELEVATION MODELS

机译:数字高程模型中垂直伪像的新型降噪算法

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Remote sensing is a technique which demands a large amount of analysis on data which may have been captured from a variety of sources. Common sources range from aerial vehicles equipped with scanning devices to sensors attached to satellites in space missions. The data acquisition, however, is commonly subject to the interference of external factors, such as particles in the atmosphere and clouds, which may lead to noise in the data. This paper presents a technique to detect the presence of such artifacts, as observed in some digital elevation model data, and an algorithm to patch them. A case study on the second version of the ASTER GDEM shows that the proposed algorithm is effective in the detection and patching of vertical artifacts and that it can be applied to different data sets in the realm of digital elevation models.
机译:遥感是一种需要对可能已从各种来源捕获的数据进行大量分析的技术。常见的信息来源包括配备扫描装置的飞行器,以及在太空任务中连接到卫星的传感器。但是,数据采集通常会受到外部因素的干扰,例如大气和云中的颗粒,这可能会导致数据中的噪声。本文提出了一种在某些数字高程模型数据中观察到的检测伪像的技术,以及一种对它们进行修补的算法。对第二版ASTER GDEM进行的案例研究表明,该算法可有效检测和修补垂直伪影,并且可以应用于数字高程模型领域中的不同数据集。

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