从高分辨率遥感影像中提取单木树冠信息能够有效提高森林资源的调查与管理水平;针对现有单木树冠提取方法对郁闭度较高的阔叶林提取精度低的问题,提出一种基于迭代H-minima改进分水岭算法的高分辨率遥感影像单木树冠提取方法;首先利用形态学开操作对图像进行平滑处理,采用Sobel算子提取梯度图像,并利用均值滤波进行去噪处理;然后利用一组h值在梯度图像上迭代识别树冠标记,利用虚假标记检测方法过滤无效标记;最后引入对称原则来限制分水岭算法的淹没过程,避免树冠标记过生长与无标记树冠合并;以高分辨率遥感影像作为数据源,同时采用传统的标记控制分水岭算法和所算法提取单木树冠,从单木位置和树冠轮廓两个方面,以及样地和单木两个尺度上对单木树冠提取的精度进行评价。结果表明:所提算法提取树冠的F测度为92.71%,比标记控制分水岭算法提高了31.99%;所提算法能够有效抑制过分割、减少欠分割,从而提高单木树冠的提取精度。

Extracting individual tree crowns in high resolution remote sensing image can improve forest inventory and management. To solve the problem that the existing individual tree crown extraction method has low accuracy in broad-leaved forest with high tree crown density, we propose an iterative H-minima watershed method for individual tree crown extraction in high resolution remote sensing images. Firstly, the morphological open operation is used to smooth the image, the Sobel operator is used to extract the gradient image, and the mean filter is used to denoise. Secondly, a set of h values are iteratively used to identify tree crown markers on gradient images, and the invalid markers are filtered by using the false marker detection method. Finally, the symmetry principle is introduced to restrict the flooding process of watershed algorithm, thus avoid the overgrowth of tree crown and combination of unmarked tree crowns. The high resolution remote sensing image is used as the data source, and the traditional marker-controlled watershed algorithm and the proposed algorithm in this paper are used to extract the single tree crown. The quality of the individual tree crown extraction is evaluated according to the single tree position and crown contours, and from both samples and individual tree scales. The results show that the F measurement of the tree crown obtained by the proposed algorithm in this paper is 92.71%, which is 31.99% higher than that of the marker-controlled watershed algorithm. This proposed algorithm can effectively suppress the over-segmentation, reduce the under-segmentation, and improve the extraction precision of the individual tree crown.