Recently, there has been increasing attention to the digital elevation model (DEM) because of its ability to learn the Earth’s surface’s topography. Freely accessible DEMs such as the Cartosat-1, shuttle radar topography mission (SRTM), light detection and ranging, and advanced spaceborne thermal emission and reflection radiometer DEM, contain large vertical errors. The errors are aggravated over multifaceted geography and cannot rectify microgeographic deviations in the moderately flat landscape. As high-accuracy DEMs have limited availability, dated low-accuracy DEMs are still used in various models, specifically in the data-sparse areas. However, it is necessary to enhance the quality of these DEMs before their use in the geomorphometric analysis. We aim to investigate the effect of noise reduction filters on DEM’s accuracy and quality. The noise reduction filters such as weighted average filter, median filter, sharpen filter, Lee sigma filter, and local sigma filter are used for noise reduction in the stereo images. The quality and accuracy of the generated DEMs are further improved by selecting an optimum number of tie points in the image matching process. The effects are assessed by correlating the surface profiles for the final DEM obtained and SRTM DEM as a reference with a resolution of 1 arc sec.

中文翻译：

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在立体影像上使用降噪滤镜以提高数字高程模型的准确性和质量

最近，由于数字高程模型（DEM）能够了解地球表面的地形，因此越来越引起人们的注意。Cartosat-1，航天飞机雷达地形任务（SRTM），光检测和测距以及先进的星载热发射和反射辐射计DEM等可自由访问的DEM包含较大的垂直误差。这些错误在多方面的地理环境中更加严重，无法纠正中等平坦景观中的微观地理偏差。由于高精度DEM的可用性有限，因此过时的低精度DEM仍用于各种模型中，尤其是在数据稀疏的区域中。但是，有必要在将这些DEM用于地貌分析之前提高其质量。我们旨在研究降噪滤波器对DEM准确性和质量的影响。降噪滤波器（例如加权平均滤波器，中值滤波器，锐化滤波器，Lee sigma滤波器和局部sigma滤波器）用于减少立体声图像中的噪声。通过在图像匹配过程中选择最佳结点数，可以进一步提高生成的DEM的质量和准确性。通过将最终获得的DEM的表面轮廓与SRTM DEM作为参考（分辨率为1弧秒）相关联来评估效果。