Advances in mathematical morphology applied to geoscience and remote sensing
Advances in mathematical morphology applied to geoscience and remote sensing
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DOI：
10.1109/tgrs.2002.804618
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发表时间：
2002-09-01
影响因子：
8.2
通讯作者：
Pesaresi, M
中科院分区：
文献类型：
--
作者：
Soille, P;Pesaresi, M
通过集中分析像素组之间的空间关系，数学形态学为我们提供了一种与基于单个像素光谱特征分析的图像处理策略互补的图像处理策略。多种形态变换可用于提取空间数据中的结构信息。因此，正如一项简短的调查所强调的，自 20 世纪 80 年代中期以来，在地球科学和遥感领域出现了一系列成功的应用。然而，数学形态学理论的最新进展在很大程度上仍未得到探索。我们在本文中表明，它们可以增强地球观测数据处理和分析的方法，以完成过滤、简化、方向分割和峰线提取等多种任务。我们还解决了过去被忽视的重要问题，以及有关给定形态过滤器对地球观测数据的适用性的问题。特别是，我们指出，在许多应用中需要自对偶甚至自互补滤波器来产生独立于搜索图像结构的局部对比度的结果。
By concentrating on the analysis of the spatial relationships between groups of pixels, mathematical morphology provides us with an image processing strategy complementary to those based on the analysis of the spectral signature of single pixels. A wide variety of morphological transformations are available for extracting structural information in spatial data. Accordingly, a stream of successful applications in geoscience and remote sensing have been reported since the mid-1980s as highlighted in a brief survey. However, recent advances in the theory of mathematical morphology still remain largely unexplored. We show in this paper that they can enhance methodologies for the processing and analysis of earth observation data for tasks as diverse as filtering, simplification, directional segmentation and crest line extraction. We also address important issues overlooked in the past and concerning the applicability of a given morphological filter to earth observation data. In particular, we point out that self-dual or even self-complementary filters are required in many applications to produce results independent of the local contrast of the searched image structures.