Phattaralerphong J, Sinoquet H
UMR PIAF INRA-UBP, Site de Crouelle, 234 Avenue du Brézet, 63039 Clermont-Ferrand Cedex 2, France.
Tree Physiol. 2005 Oct;25(10):1229-42. doi: 10.1093/treephys/25.10.1229.
We developed a method for reconstructing tree crown volume from a set of eight photographs taken from the N, S, E, W, NE, NW, SE and SW. This photographic method of reconstruction includes three steps. First, canopy height and diameter are estimated from each image from the location of the topmost, rightmost and leftmost vegetated pixel; second, a rectangular bounding box around the tree is constructed from canopy dimensions derived in Step 1, and the bounding box is divided into an array of voxels; and third, each tree image is divided into a set of picture zones. The gap fraction of each picture zone is calculated from image processing. A vegetated picture zone corresponds to a gap fraction of less than 1. Each picture zone corresponds to a beam direction from the camera to the target tree, the equation of which is computed from the zone location on the picture and the camera parameters. For each vegetated picture zone, the ray-box intersection algorithm (Glassner 1989) is used to compute the sequence of voxels intersected by the beam. After processing all vegetated zones, voxels that have not been intersected by any beam are presumed to be empty and are removed from the bounding box. The estimation of crown volume can be refined by combining several photographs from different view angles. The method has been implemented in a software package called Tree Analyzer written in C++. The photographic method was tested with three-dimensional (3D) digitized plants of walnut, peach, mango and olive. The 3D-digitized plants were used to estimate crown volume directly and generate virtual perspective photographs with POV-Ray Version 3.5 (Persistence of Vision Development Team). The locations and view angles of the camera were manually controlled by input parameters. Good agreement between measured data and values inferred from the photographic method were found for canopy height, diameter and volume. The effects of voxel size, size of picture zoning, location of camera and number of pictures were also examined.
我们开发了一种从从北、南、东、西、东北、西北、东南和西南方向拍摄的八张照片重建树冠体积的方法。这种摄影重建方法包括三个步骤。首先，从每个图像中最顶部、最右侧和最左侧植被像素的位置估计树冠高度和直径；其次，根据第一步得出的树冠尺寸构建围绕树木的矩形边界框，并将该边界框划分为一组体素；第三，将每棵树的图像划分为一组图像区域。通过图像处理计算每个图像区域的间隙分数。植被覆盖的图像区域对应于小于1的间隙分数。每个图像区域对应于从相机到目标树的光束方向，其方程根据图像上的区域位置和相机参数计算得出。对于每个植被覆盖的图像区域，使用光线-盒子相交算法（Glassner，1989）计算光束相交的体素序列。处理完所有植被覆盖区域后，未被任何光束相交的体素被假定为空，并从边界框中移除。通过组合不同视角的多张照片可以优化树冠体积的估计。该方法已在一个名为Tree Analyzer的用C++编写的软件包中实现。使用核桃、桃子、芒果和橄榄的三维（3D）数字化植物对该摄影方法进行了测试。3D数字化植物用于直接估计树冠体积，并使用POV-Ray 3.5版本（视觉持久性开发团队）生成虚拟透视图照片。相机的位置和视角由输入参数手动控制。在树冠高度、直径和体积方面，测量数据与从摄影方法推断的值之间发现了良好的一致性。还研究了体素大小、图像分区大小、相机位置和照片数量的影响。
