【摘要】 为了充分挖掘无人机图像,快速有效地提取树木信息,利用无人机数据生成的正射影像作为研究对象,提出一种Mean Shift算法和分水岭分割算法相结合的林木株数提取方法。该方法利用Mean Shift算法对从RGB图像中提取的G通道图像进行有效地聚类和平滑处理,然后将其输入到结合形态学运算以及欧氏距离变换的分水岭分割算法中进行单木检测和树木株数提取。实验结果表明:与目视解译并计数的10块样地结果相比,本文研究方法的树木株数提取精度在92.74%左右。该方法可以有效地检测单木及提取树木株数,并且具有较好的提取精度。更多还原

【Abstract】 To fully explore unmanned aerial vehicle(UAV) imagery and extract forest information efficiently, this study used an orthophoto derived from UAV data to propose a tree counts extraction method combining the Mean Shift algorithm and watershed segmentation algorithm. The method utilized the Mean Shift algorithm to efficiently cluster and smooth the G channel images extracted from RGB images. These images were then fed into the watershed method which combined morphology operation and Euclidean distance for individual treetop detection and tree count extraction. The result showed that the tree counts extraction accuracy of the algorithm in this paper was approximately 92.74% when the result was compared to ten manually marked and counted plots. The result demonstrated that this method was efficient to detect individual tree and extract tree counts, and had better detection accuracy.更多还原