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A Coupled Co-Occurrence Matrix/Multi-Scale Segmentation Method to Extract Water from High Resolution Remote Sensing Image

机译:耦合共生矩阵/多尺度分割方法从高分辨率遥感影像中提取水

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This study developed a coupled co-occurrence matrix/multi-scale segmentation method to improve extraction precision of water from high-resolution remote sensing images. Two images of Kunming city (subject A & B) were obtained from Quick Bird image gallery, pre-processed by co-occurrence matrix, and then multi-scale segmented based on inherent geometrical and geographical attributes. Water encompassed by the ring roads of the city was extracted via object-oriented information analysis with successfully removal of all shadows. Results showed that water extraction precisions had significantly increased for both subject A (68.6% → 95.2%) and B (63.0% → 92.3%), indicating superior performance of the proposed method in extracting water from complex urban environment.
机译:这项研究开发了一种共现矩阵/多尺度相结合的分割方法,以提高从高分辨率遥感影像中提取水的精度。从“快鸟”图像库中获取两幅昆明市的图像(主题A和B),并用共现矩阵进行预处理,然后根据固有的几何和地理属性进行多尺度分割。通过面向对象的信息分析,成功去除了所有阴影,提取了城市环城公路所包围的水。结果表明,受试者A(68.6%→95.2%)和受试者B(63.0%→92.3%)的水提取精度均显着提高,表明该方法在复杂的城市环境中提取水的性能优越。

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