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Combining Satellite Images with Feature Indices for Improved Change Detection

机译：结合卫星图像和特征指标以改善变化检测

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This paper presents a novel approach to detect changes in satellite images taken from the same location at different timestamps. Different change detection methods are applied to multispectral satellite images taken with the Worldview-2 (WV-2) satellite, as well as to several of their feature indices such as normalized difference vegetation index (NDVI), normalized difference soil index (NDSI), non-homogeneous feature index (NHFD) and red-blue ratio (R/B). Besides, an additional image is used to remove temporary changes like vehicles, persons etc. The combination of changes is computed with a set of pixel-wise operations, and morphological filters are applied to improve the final change map. The combination of the satellite images with their feature indices proved to produce better results than computing the changes independently. This paper summarizes the methodology and presents the results obtained.
机译：本文提出了一种新颖的方法来检测在不同时间戳下从同一位置拍摄的卫星图像的变化。将不同的变化检测方法应用于用Worldview-2（WV-2）卫星拍摄的多光谱卫星图像，以及其某些特征指标，例如归一化差异植被指数（NDVI），归一化差异土壤指数（NDSI），非均匀特征指数（NHFD）和红蓝比率（R / B）。此外，附加图像用于去除临时更改，例如车辆，人员等。更改的组合是通过一组按像素操作来计算的，并且应用了形态过滤器来改进最终更改图。事实证明，将卫星图像与其特征索引相结合比单独计算变化产生更好的结果。本文总结了方法，并介绍了获得的结果。

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