王爱萍, 王树根, 吴会征. 利用分层聚合进行高分辨率遥感影像多尺度分割[J]. 武汉大学学报 ( 信息科学版), 2009, 34(9): 1055-1058.
引用本文: 王爱萍, 王树根, 吴会征. 利用分层聚合进行高分辨率遥感影像多尺度分割[J]. 武汉大学学报 ( 信息科学版), 2009, 34(9): 1055-1058.
WANG Aiping, WANG Shugen, WU Huizheng. Multiscale Segmentation of High Resolution Satellite Imagery by Hierarchical Aggregation[J]. Geomatics and Information Science of Wuhan University, 2009, 34(9): 1055-1058.
Citation: WANG Aiping, WANG Shugen, WU Huizheng. Multiscale Segmentation of High Resolution Satellite Imagery by Hierarchical Aggregation[J]. Geomatics and Information Science of Wuhan University, 2009, 34(9): 1055-1058.

利用分层聚合进行高分辨率遥感影像多尺度分割

Multiscale Segmentation of High Resolution Satellite Imagery by Hierarchical Aggregation

  • 摘要: 针对高分辨率遥感影像的特点,提出了一种基于分层聚合的多尺度分割算法。该算法首先对遥感影像进行分水岭变换,然后对初始分割区域构建底层加权无向图,利用代数多重网格解法(AMG)在尺度空间求解最优的图割测度,整个分割过程自动得到了多尺度的分割结果。实验表明,该方法能够得到满意的分割结果,并具有较高的自动化程度。

     

    Abstract: A multiscale segmentation approach by hierarchical aggregation(SHA) is proposed,which is inspired by the idea of SWA(segmentation by weighted aggregation).SHA is more suitable for high resolution satellite imagery through some improvement over SWA.The imagery is first preprocessed by watershed transformation so that a graph is constructed from the segments by their spectral distance.Then a bottom-up aggregation framework derived from algebraic multigrid solver that is used to minimize a graph cut measure.Region based features(e.g.texture,shape,etc.) are accumulated conveniently during the aggregation process and implementation also is faster than SWA.

     

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