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Multitemporal change detection for SAR imagery

机译:SAR影像的多时相变化检测

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Abstract: This paper describes an optimized approach to identifying changes within a sequence of ESR images of Heathrow airport. We show that joint annealed segmentation avoids the false detections encountered along the edges of structural features when detecting differences between segmented scenes. This leads to an optimized change detection process, which can be applied in the detection of aircraft and vehicles around the airfield, even though the resolution of ERS image is only 25 m (range) by 6.25 m (azimuth). In addition, we show how joint segmentation of the coherence image between pairs of 35-day repeats yield an appreciable improvement in a false color change representation based on two amplitude images and their coherence image.!6
机译:摘要:本文介绍了一种用于识别希思罗机场ESR图像序列中变化的优化方法。我们显示,联合退火分割可以避免在检测分割场景之间的差异时沿结构特征边缘遇到的错误检测。这导致优化的变化检测过程,即使ERS图像的分辨率仅为25 m(范围)乘以6.25 m(方位角),也可以将其应用于飞机场周围的飞机和车辆的检测。此外,我们展示了如何基于两幅振幅图像及其相干图像,对成对的35天重复之间的相干图像进行联合分割,从而显着改善假色变化表示形式!6

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