利用多特征进行航空影像建筑物提取

Regular Building Extraction from High Resolution Image Based on Multilevel-Features

  • 摘要: 高分辨率遥感影像在不同的尺度下表现出不同的特征,根据这一特性,提出了一种基于多层次特征的航空影像规则建筑物提取方法。该方法先利用大尺度特征——方向梯度直方图(histograms of oriented gradient,HOG)特征对建筑物进行识别,然后提出了一种小尺度特征——纹理和光谱融合特征,该特征能够有效地将HOG特征识别结果中的道路、草地等非建筑物剔除,最终获取建筑物边缘信息。实验结果表明,该方法不仅对矩形建筑物有较好的提取效果,对结构复杂的规则建筑物也有较好的提取效果。

     

    Abstract: High-resolution remote sensing images reveal dissimilar distinguishable features at different scales. Based on this characteristic of high-resolution remote sensing images, a new method of extracting buildings based on multilevel feature in aerial images was developed by associating scales with features. In the case of a large-scale feature, histograms of oriented gradient (HOG), were used to recognize rough buildings areas. The areas maybe include the grass, roads and some other non-building information. In order to remove these non-building surface features, fused spectral and texture features (T-B) is proposed at the small scale. The T-B feature is used to process the results of the first recognized HOG results. Experimental results demonstrate that the new feature has a good effect. Edge information of buildings was obtained and the results show that our proposed algorithm can extract both rectangular and complex buildings in different area remote sensing images well.

     

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