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METHOD OF EXTRACTING WAREHOUSE IN PORT FROM HIERARCHICALLY SCREENED REMOTE SENSING IMAGE

机译:从分级筛选的遥感图像中提取港口仓库的方法

摘要

A method of extracting a warehouse in a port from a hierarchically screened remote sensing image includes the following steps: first, recognizing a texture feature of a remote sensing image and extracting edge lines of a coast of a port; then, selecting a sample of an optional irregular texture region and forming, through a CA transformation, principal component images of different hierarchies by taking a ratio of a between-class difference to an intra-class difference being maximum as an optimization condition; sequentially, extracting a correlation relationship of the warehouse in the port, and forming a feature point set with recognized warehouses to be analyzed; and last, extracting a feature of a visually sensitive image through a scene image to obtain a feedback selection of a real scene image to extract the warehouse in the port accurately.
机译:一种从分层筛选的遥感图像中提取港口内仓库的方法,包括以下步骤:首先,识别遥感图像的纹理特征,并提取港口的海岸边缘线。然后,选择可选的不规则纹理区域的样本,并通过CA变换,以类间差与类内差的比最大为优化条件,形成不同层次的主成分图像。依次提取港口中仓库的关联关系,并与已识别的待分析仓库形成特征点集。最后,通过场景图像提取视觉敏感图像的特征,以获得对真实场景图像的反馈选择,以准确提取港口的仓库。

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