Detection and reconstruction of human scale features from high resolution interferometric SAR data
Detection and reconstruction of human scale features from high resolution interferometric SAR data
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DOI：
10.1109/icpr.2000.902916
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发表时间：
2000-09
期刊：
影响因子：
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通讯作者：
R. Bolter;F. Leberl
中科院分区：
文献类型：
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作者：
R. Bolter;F. Leberl
与光学成像相比，现代高分辨率IFSAR传感器可以从30厘米到10厘米的像素大小的单个飞行路径提供强度图像和相应的干涉高度和相干性数据。由于SAR传感器的全天候、昼夜适用性，可以很容易地获得短时间内的多个视图。然而，许多图像用户发现很难“读取”雷达图像。它们不同于人类自然的视觉印象，也不同于人们所熟悉的光学图像所传达的类比。我们的工作目标是将雷达数据转换为地形模型，并将这些模型渲染成类似于人类视觉系统所代表的光学传感方法。因此，有必要将来自所有IFSAR数据源的多个视图和测量数据进行智能组合，以帮助克服SAR数据固有的问题，例如模糊、斑点、停留和阴影。使用基本的图像分析方法，我们在本文中提出了第一个完全自动化的方法，将建筑物与IFSAR数据集中的其他物体分开。使用简单的建筑模型重建建筑物形状，并将结果与光学图像的测量结果进行比较。
In contrast to optical imagery, modern high resolution IFSAR sensors deliver intensity images and corresponding interferometric height and coherence data from a single flight path at pixel sizes of 30 cm to 10 cm. Due to the all-weather, day-night applicability of SAR sensors, multiple views over short time can be easily obtained. However, many image users find it difficult to "read" radar images. They differ from the natural human visual impression and the familiar analogy communicated by optical imagery. The goal of our work is to convert radar data into models of the terrain and render those models in analogy to the optical sensing approach that the human visual system represents. Therefore intelligent combinations of multiple views and measurements from all IFSAR data sources available are necessary to help to overcome problems inherent in the SAR data as e.g., blur, speckle, layover and shadow. Using basic image analysis methods we present in this paper our first fully automated approach to separate buildings from other objects in an IFSAR dataset. The building shapes are reconstructed using a simple building model and the results are compared to measurements made from optical imagery.