Segmentation of High Resolution Imagery over Urban Area Using Watershed Transformation and Stratified Region Merging
Segmentation of High Resolution Imagery over Urban Area Using Watershed Transformation and Stratified Region Merging
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发表时间：
2014
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通讯作者：
Cairns Ca
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作者：
Cairns Ca
鉴于基于分水岭变换的图像分割方法通常会产生明显的过分割，并且城市地区的高分辨率图像表现出一些独特的特征，作者提出了一种分层区域合并方法来优化分水岭变换最初产生的分割结果。采用多通道分水岭变换来生成初始分割结果。通过对城市地区不同地面物体的内部光谱变化进行定量分析，将图像分层为多层。区域合并在每一层中单独进行。通过聚合这些层的分割结果获得最终的分割结果。利用北京地区的QuickBird图像，通过与现有的流域分割方法在目视检查、定量测量和在城市土地覆盖分类中的应用进行比较，对所提出的方法进行了评估。实验结果表明，该方法优于现有方法，适用于城市地区高分辨率图像的分割。
Given that watershed transform based image segmentation methods usually produce obvious over-segmentation, and the high resolution imagery of urban areas shows some peculiar characteristics, the authors propose a hierarchical region merging method to optimize the segmentation results initially produced by watershed transformation. A multi-channel watershed transformation was adopted to generate an initial segmentation result. Through quantitative analysis of internal spectral variability of different ground objects in urban areas, the image was stratified to several layers. Region merging was separately conducted in each layer. A final segmentation result was obtained by aggregating segmentation results from these layers. The proposed method was evaluated by comparing with the existing watershed segmentation method in terms of visual inspection, quantitative measures and applications in urban land cover classification, using a QuickBird image of Beijing area. The experimental results indicate that the proposed method outperforms the existing method and it is suitable for segmentation of high resolution imagery over urban areas.