论文标题
卫星图像中的对象描述
Object Delineation in Satellite Images
论文作者
论文摘要
机器学习被广泛应用于分析诸如分类和特征检测等问题的卫星数据。与传统的图像处理算法不同，地理空间应用需要将检测到的对象从栅格形式转换为地理空间矢量形式，以进一步分析它。该宝石提供了一种简单而轻的算法，用于描述以ML算法为标记的像素，以从卫星图像中提取地理空间对象。提出的算法是准确的，用户可以根据应用程序需求进一步应用简化和近似。
Machine learning is being widely applied to analyze satellite data with problems such as classification and feature detection. Unlike traditional image processing algorithms, geospatial applications need to convert the detected objects from a raster form to a geospatial vector form to further analyze it. This gem delivers a simple and light-weight algorithm for delineating the pixels that are marked by ML algorithms to extract geospatial objects from satellite images. The proposed algorithm is exact and users can further apply simplification and approximation based on the application needs.
