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CLASSIFYING MICROWAVE RADAR IMAGES USING DECISION BASED DATA FUSION

机译:使用基于决策的数据融合对微波雷达图像进行分类

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摘要

Four different data fusion methods for classifying SAR images were tested and compared. Test area was Helsinki region in Southern Finland and test data 14 ERS-1/2 Tandem pairs. The best method was a method where a posteriori probabilities of lower spatial resolution classification are used as a priori probabilities of higher resolution classification. The increase of overall accuracy was 7-14 %-units depending on date and 10.4% on average when compared to original Tandem pairs. Median filtering increased classification accuracy, but not that much when data fusion methods were used. This means that the need of spatial filtering can be at least partially compensated using data fusion of different spatial resolution images.
机译:测试和比较了四种不同的SAR图像分类数据融合方法。测试区域为芬兰南部的赫尔辛基地区,测试数据为14对ERS-1 / 2串联。最好的方法是将较低空间分辨率分类的后验概率用作较高分辨率分类的先验概率的方法。与原始Tandem对相比,根据日期的总体准确性提高了7-14%-单位,平均提高了10.4%。中值过滤提高了分类精度,但使用数据融合方法时并没有那么多。这意味着可以使用不同空间分辨率图像的数据融合至少部分地补偿空间滤波的需要。

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