用于地面可视化的DEM四叉树改进

四叉树表示在数字高程模型(DEM)的压缩存储和地面可视化中占有非常重要的地位E此文吸收了DEM 普通四叉树表示和塔形分层表示的优点，提出了一种改进的四叉树结构。它主要是在结点的数据域中增加了高程 最大值和最小值项，并把四叉树线索化了。经过改进的四叉树结构使DEM在地面可视化中进行的光线追踪时，光线追踪效率得到了提高。     

一种基于四叉树的TIN的LOD算法

通过在不规则采样点集上构建一个四叉树结构，并联合基于四叉树的LOD算法和基于TIN的三角网简化算法，提出并实现了一种TIN的LOD算法。意在把适用于格网数据的高效方法应用于不规则采样点集，得到地形的一个高效的多分辨率表达。     

基于自适应四叉树的地形LOD算法

大数据动态地形三维可视化需要使用分层细节技术(LOD)简化模型,提高三维可视化效率,而四叉树可以优化复杂数据的数据结构.首先讨论了基于自适应四叉树实现LOD的一般方法,详细探讨了模型连接的三角扇绘制法;然后针对四叉树结构多分辨率表示的特点,提出了一种基于自适应四叉树节点属性修改,实现LOD模型的连续无缝连接的方法;最后使用提出的方法,实现了一幅1∶ 50000地形图范围的三维可视化,有效提高了动态显示效果.     

视相关地形多分辨率模型在飞行仿真中的应用

对于飞行仿真中海量地形数据,现有的软硬件无法直接对其进行实时连续的绘制,采用视点相关的层次细节模型可以有效地提高实时绘制的性能.该文针对飞行仿真中大地形实时显示问题,对现有的视点相关多分辨率模型算法进行了改进,采用四叉树结构来表示地形,给出了节点的数据结构和构建四叉树的算法;提出了一种新的细节层次选择误差度量标准;实现了视点相关的连续多分辨率地形网格的简化和实时绘制.     

WebGIS中多维空间数据多尺度表达索引结构*

针对现有数据结构无法支持WebGIS中多维空间数据的多尺度表达,提出了一种改进的数据结构：a)主树由金字塔层级结构规则分割的区域四叉树索引结构变形而来;b)具有支持多维数据的重叠子树结构;c)利用树的深度反映空间分辨率的变化;d)主树的所有节点均为空间对象载体,子树的节点为多维数据单元。分析了该索引产生的必要性,对该索引结构进行描述,并着重对该索引结构中的数据生成算法、多维数据支持和搜索过程进行了讨论。针对相同数据源,使用本结构与图层表达法进行对比实验,结果表明,该索引方法能对WebGIS中海量多维空间数     

图像四叉树剖分下的自适应数字水印算法

提出了一种图像四叉树矩形剖分下的自适应数字水印算法。通过对原始图像在多个尺度上进行最小二乘多项式逼近,将图像进行非均匀剖分,并以四叉树结构的形式进行表达。该四叉树结构既实现了对原始图像的逼近,同时携带了图像的纹理结构信息。通过统计各子区域上的剖分网格数目,计算不同区域上水印嵌入的强度,从而实现自适应数字水印方案。实验结果表明,该算法具有良好的透明性和顽健性。     

一种视点相关的多分辨率地形实时绘制方法

本文提出了一种基于视点的地形分块策略，并以四叉树结构来组织地形分块，提出了一种利用受限四叉树对地形网格实时剖分的改进算法，实现了与视点相关的连续多分辨率地形网格的简化和实时绘制。     

基于八叉树空间分割的NURBS曲面重构方法

对三维模型和点云曲面重构方法进行深入研究,根据应用特点提出八叉树空间分割和N U RBS曲面重构方法。利用八叉树的快速收敛特性对三维实体的点云数据进行分割、精简,采用N U RBS方法对局部网格曲面进行重构;采用八叉树和四叉树相混合的数据结构,渐进地进行网格曲面的重构。存储结构采用扩展式八叉树结构,编码采用8进制前缀编码方法。利用O penG L设计一个实验模型系统验证了该算法的可行性和有效性。     

一种基于四叉树的空域图像选择加密算法

提出一种基于四叉树结构的选择加密算法。对空域图像位平面采用四叉树编码,根据四叉树编码的结构特点对数据进行置乱和选择加密,对加密算法进行加密数据量分析和安全性评估。实验结果表明,该算法安全性较高,其空域图像的加密数据量为一般加密算法的50%左右。     

基于IEC 61850的内存数据库的组织

针对构造基于IEC61850规范的内存数据库的问题,分析了将非面向对象的内存数据库应用到IEC61850规范的缺点,结合IEC61850的变电站配置语言的特点,说明了基于面向对象的内存数据库构成树形结构。描述了基于二叉树结构的内存数据库。在传统多叉树的基础上,提出了间接多叉树结构。该结构引入了有序数组,通过有序数组查找数据。结合变电站自身的特点,通过分析二叉树和间接多叉树的时间复杂度和空间复杂度,论证了间接多叉树结构具有更好的性能,更适合基于IEC61850内存数据库的组织。     

A top-down quadtree traversal algorithm

Many standard image processing operations can be implemented using quadtrees as a simple tree traversal where, at each terminal node, a computation is performed involving some of that node's neighbors. Most of this work has involved the use of bottom-up neighbor-finding techniques which search for a nearest common ancestor. Recently, top-down techniques have been proposed which make use of a neighbor vector as the tree is traversed. A simplified version of the top-down method for a quadtree in the context of a general-purpose tree traversal algorithm is presented. It differs, in part, from prior work in its ability to compute diagonally adjacent neighbors rather than just horizontally and vertically adjacent neighbors. It builds a neighbor vector for each node using a minimal amount of information. Analysis of the algorithm shows that its execution time is directly proportional to the number of nodes in the tree. However, it does require some extra storage. Use of the algorithm leads to lower execution time bounds for some common quadtree image processing operations such as connected component labeling.     

Perception-motivated multiresolution rendering on sole-cube maps

This paper presents a novel GPU-based multiresolution rendering on sole-cube maps (SCMs), which is a variant of geometry images built upon spherical parameterization. Given spherical parametrization of a manifold mesh, the sphere domain is gnomonically projected to a closed cube, which constitutes the 6-chart sole-cube maps. A quadtree structure of SCMs and normal map atlas are then constructed by using the regular re-sampling. Then, by packing the quadtree nodes into the SCMs texture atlas, a new parallel multiresolution rendering is processed on the latest GPU in two rendering passes: the multiresolution node selection in fragment shader; the triangulation in vertex shader followed by the node culling operation in geometry shader. The proposed approach generates adaptive mesh surfaces dynamically, and can be fully implemented in GPU parallelization. The proposed scheme alleviates the computing load of multiresolution mesh refinement on CPU, and our GPU-based multiresolution rendering is demonstrated with a variety of examples. Our user study confirmed that the visual quality of the SCMs multiresolution rendering, in comparison with the meshes/geometry images rendering, is also highly efficient especially for complex models in large-scale virtual environment.     

Multiresolution image registration based on tree data structures

This paper presents a new approach for image registration based on the partitioning of the two source images in binary-space and quadtree structures, obtained with a maximum mutual information gain algorithm. Two different implementation approaches that differ in the level at which information is considered have been studied. The first works at pixel level using the simplified images directly, while the second works at node level dealing with the tree data structure. The obtained results show an outstanding accuracy and robustness of the proposed methods. In particular, the use of binary-space partitioned images drastically reduces the grid effects in comparison with regular downsampled images. An important advantage of our approach comes from the reduced size of the data structures corresponding to the simplified images, which makes this method appropriate to be applied in a multiresolution framework and telemedicine applications.     

Linkless Octree Using Multi‐Level Perfect Hashing

The standard C/C++ implementation of a spatial partitioning data structure, such as octree and quadtree, is often inefficient in terms of storage requirements particularly when the memory overhead for maintaining parent‐to‐child pointers is significant with respect to the amount of actual data in each tree node. In this work, we present a novel data structure that implements uniform spatial partitioning without storing explicit parent‐to‐child pointer links. Our linkless tree encodes the storage locations of subdivided nodes using perfect hashing while retaining important properties of uniform spatial partitioning trees, such as coarse‐to‐fine hierarchical representation, efficient storage usage, and efficient random accessibility. We demonstrate the performance of our linkless trees using image compression and path planning examples.     

基于OBB树的无网格几何数据处理

提出一种新的基于有向包围盒树(Oriented Boundmg Box,OBB树)的处理无网格几何数据方案.与最常用的八叉树比较,它具有三方面优点:首先,OBB树反映了统计意义上的几何模型空间分布,它不仅提供了辅助的层次结构,其本身还可以用于生成原始几何模型的形状逼近;其次,OBB树的节点数目和所需内存比八叉树少,且更贴近几何模型;其三,遍历OBB树的代价略高于八叉树,收敛速度却更快.针对点云模型,作者将OBB树结构应用于点云模型的自适应绘制.实验结果验证了OBB树的上述优点.     

基于Dandelion编码生成有界树宽CP-nets

针对条件偏好网络（CP-nets）图模型在进行推理运算时的高时间复杂度的问题,提出了一种基于Dandelion编码生成有界树宽的CP-nets（BTW-CP-nets Gen）算法。首先,通过Dandelion编码与树宽为k的树结构（k-tree）之间的双向映射原理推导出Dandelion编码与k-tree之间的解码与编码算法,实现编码与树结构的一对一映射;其次,利用k-tree来约束CP-nets结构的树宽,并利用k-tree的特征树得到了CP-nets的有向无环图结构;最后,利用离散多值函数的双射计算出各CP-nets结构节点的条件偏好表,然后针对生成的有界树宽CP-nets进行占优查询检测。理论分析和实验数据表明,与Pruffer编码生成k-tree（Pruffer code）算法相比,BTW-CP-nets Gen算法的运行时间在生成简单结构和复杂结构时的下降幅度分别为21.1%和30.5%;而BTW-CP-nets Gen算法所生成的图模型在进行占优查询时的节点遍历比在简单结构和复杂结构上分别提高了18.48%和29.03%。BTW-CP-nets Gen算法在更短的时间内,占优查询时遍历的节点率更高。可见,BTW-CP-nets Gen算法在图模型的推理中能够有效提高算法效率。     

基于互关联后继树的XML索引技术

提出了一种新的根树节点编码方法——基于叶序区间的节点编码(LOINS)．编码方法只需对根树后序遍历一次即可完成,能实现常数时间内对任意两个树节点间前后代关系的判断．同时,结合互关联后继树模型(IRST)的标引性、可压缩性等特点,提出基于IRST的根树索引模型Ist3aRTI-Ⅰ,及对该模型空间优化的索引模型IstBaRTI-Ⅱ．IsBaRTI-Ⅰ,Ⅱ采用树节点名称(标签)及其在根树(XML文档树)中的出现计数索引节点间的父子关系和节点叶序区间编码,实现索引结构和节点编码的相互统一,IsBaRTI-Ⅰ,Ⅱ索引建立时间、空间代价小,可快速查询满足XPath表达式在XML文档树中的节点序列和路径．     

Multiresolution Compression and Visualization of Global Topographic Data

We present a multiresolution model for terrain surfaces which is able to handle large-scale global topographic data. It is based on a hierarchical decomposition of the sphere by a recursive bisection triangulation in geographic coordinates. Error indicators allow the representation of the data at various levels of detail and enable data compression by local omission of data values. The resulting adaptive hierarchical triangulation is stored using a bit code of the underlying binary tree and additionally, relative pointers which allow a selective tree traversal. This way, it is possible to work directly on the compressed data. We show that significant compression rates can be obtained already for small threshold values. In a visualization application, adaptive triangulations which consist of hundreds of thousands of shaded triangles are extracted and drawn at interactive rates.     

Geometric probing of dense range data

A new method is presented for the efficient and reliable pose determination of 3D objects in dense range image data. The method is based upon a minimalistic Geometric Probing strategy that hypothesizes the intersection of the object with some selected image point, and searches for additional surface data at locations relative to that point. The strategy is implemented in the discrete domain as a binary decision tree classifier. The tree leaf nodes represent individual voxel templates of the model, with one template per distinct model pose. The internal nodes represent the union of the templates of their descendant leaf nodes. The union of all leaf node templates is the complete template set of the model over its discrete pose space. Each internal node also encodes a single voxel which is the most common element of its child node templates. Traversing the free is equivalent to efficiently matching the large set of templates at a selected image seed location. The method was implemented and extensive experiments were conducted for a variety of combinations of tree designs and traversals under isolated, cluttered, and occluded scene conditions. The results demonstrated a tradeoff between efficiency and reliability. It was concluded that there exist combinations of tree design and traversal which are both highly efficient and reliable     

MSKD: multi-split KD-tree design on GPU

We present a novel parallel acceleration structure construction and traversal algorithm designed to efficiently exploit the massive parallel computing cores on the Graphic Processing Unit(GPU) to improve the render performance. Our associated data structure is called multi-split KD-tree or MSKD, which focuses on fast generating and efficiently traveling multiple child nodes hierarchy in parallel. At build-time, we introduce a multi-split node generation method to split along three-dimension axes into eight child nodes once, and gather quickly high-quality child nodes even at early construction phase. During traversal, we propose a progressive traversal to fast decide the visiting order for multiple child nodes. Then, we use a dynamic ray transfer to adaptively drive the traversal tasks execution on the GPU. Our experiments with this hierarchy show the construction and traversal performance improvement for ray tracing using MSKD compared to previous methods.