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The Extraction of Individual Tree-Crown in Aerial Digital Camera Imagery

机译:在空中数码相机图像中的单个树冠提取

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A high spatial resolution remote sensing image provides a huge amount of data about our earth surface in more details, and makes it possible to estimate forest and tree parameters directly from aerial image. In this research the segmentation algorithm of region-merging technique was used for the identification of the individual tree crown. Fuzzy logic membership function and nearest neighbor classifier were used for the extraction of tree canopy information. The crown canopy was extracted firstly based on the multi-scale segmentation, fuzzy logic classification, and objects merge based on the class. A segmentation of tree crown mode was conducted for the individual tree crown. To get satisfying outcome, morphological reconstruction based on fuzzy logic functions, such as the feature of the area threshold and relative border to, were used to eliminate some false polygons. The results from the image-derived and field measured tree crown comparisons in this paper show that there was significant correlation, with the correlation coefficients varying from 0.69 to 0.82. Most of the tree crowns were underestimated because of the influence of shadow and crown overlap. And further research will concentrate on individual trees with little crown overlap and full rounded crowns.
机译:高空间分辨率遥感图像在更多细节中提供了关于我们地球表面的大量数据,并且可以直接从航拍图像估计森林和树参数。在本研究中,区域合并技术的分割算法用于识别各个树冠。模糊逻辑隶属函数和最近的邻分类器用于提取树冠的信息。基于多尺度分割,模糊逻辑分类和基于类的对象合并,首先提取冠长。为各个树冠进行树冠模式的分割。为了获得令人满意的结果,基于模糊逻辑功能的形态重建,例如区域阈值和相对边界的特征,用于消除一些虚假多边形。本文中的图像推导和场测量树冠比较的结果表明,相关系数从0.69到0.82变化显着相关。由于阴影和冠重叠的影响,大多数树冠被低估了。进一步的研究将集中在具有小皇冠重叠和全圆形冠的个体树上。

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