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Classification of Remote Sensing Data With Morphological Attribute Profiles: A decade of advances
IEEE Geoscience and Remote Sensing Magazine ( IF 16.2 ) Pub Date : 2021-03-01 , DOI: 10.1109/mgrs.2021.3051859
Deise Santana Maia , Minh-Tan Pham , Erchan Aptoula , Florent Guiotte , Sebastien Lefevre

Morphological attribute profiles (APs) are among the most prominent methods for spatial–spectral pixel analysis of remote sensing images. Since their introduction a decade ago to tackle land cover classification, many studies have been contributed to the state of the art, focusing not only on their application to a wider range of tasks but also on their performance improvement and extension to more complex Earth observation data.

中文翻译:

具有形态属性剖面的遥感数据分类:十年的进步

形态属性剖面(APs)是遥感图像空间光谱像素分析最突出的方法之一。自从十年前引入土地覆盖分类以来,许多研究都为最先进的技术做出了贡献,不仅关注它们在更广泛任务中的应用,而且关注它们的性能改进和扩展到更复杂的地球观测数据.
更新日期:2021-03-01
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