Predicting old-growth tropical forest attributes from very high resolution (VHR)-derived surface metrics

Old-growth tropical forests are increasingly vanishing worldwide. Although the accurate quantification of tropical old-growth forests attributes is essential to understand, manage, and conserve their high diversity and biomass, conducting this task over large areas and at fine detail is not only expensive and time consuming, but also often practically impossible. This calls for the search for more efficient alternatives, particularly those based on remote sensing. In this study, we evaluate the potential of several surface metrics (tone and texture) extracted from very high resolution (VHR) satellite imagery to model the structural and diversity attributes of a tropical dry forest (TDF) in southern Mexico. We constructed simple linear models that used each forest attribute as dependent variables, and the tone and texture metrics extracted from several bands, the panchromatic (resolution = 0.5 m), red (R), infrared, and two vegetation indices (normalized difference vegetation index (NDVI), enhanced vegetation index (EVI); resolution = 2 m), of a VHR image (GeoEye-1) as predictive variables. The significance of the models including one, two, two and its interaction, and three image metrics was evaluated by comparing them with null models. The structural characteristics of the TDF (basal area (BA), mean height, stem density) showed the highest modelling potential, with the goodness-of-fit (R²) values ranging from 0.58 to 0.66. Conversely, no significant models were obtained for total crown area (TCA) and all diversity attributes. Our results show that remote-sensing metrics detect the spatial variation in the structural attributes of this old-growth TDF better than they detect the variation in its diversity. Our ability to model forest attributes at large scales at fine detail (sampling plots <0.2 ha) can be much improved by combining the use of VHR imagery with an array as wide as possible of the image surface metrics, including both tone and texture.     

Water droplet properties on periodically structured superhydrophobic surfaces: a lattice Boltzmann approach to multiphase flows with high water/air density ratio

Surface roughness affects the contact angle (CA) due to the increased area of solid–liquid interface and due to the effect of sharp edges of rough surfaces. Roughness may also lead to another non-wetting regime, by forming a composite solid–liquid–air interface between the water and the textured surface; this composite interface exhibits strong water repellency due to the various pockets of air entrapped between the surface textures. The contact between water and a hydrophobic textured surface leads to one of these two regimes depending on the thermodynamics stability of the regimes. In this study, the projection method of lattice Boltzmann method is used to analyze the large density difference at the air and water interface. The method is applied to simulate two-phase flows with the density ratio of up to 1,000. A numerical model is presented to provide a relationship between roughness and CA, which is used to develop optimized texture topography and create a biomimetic superhydrophobic surface. The numerical models encompass the effects of contact area, solid–liquid–gas composite interface and shape edges. The models are reused to analyze different possible roughness distributions and to calculate the effect of the cross-sectional area of pillars, including rectangular, triangular, cross, and pyramidal pillars. The energy barrier is investigated to predict the position of the transition between the Cassie and Wenzel regime observed for each roughness parameter as well as a theoretical free surface energy model.     

基于细节迁移的快速外存模型简化方法

现有的快速外存模型简化方法一般是对模型进行近似均匀采样,无法根据细节分布对模型进行不同程度的简化,从而对于细节分布非均匀的模型失真较大.给出一种快速的外存模型简化方法,用于对无法一次装入内存的大型几何模型进行简化,大大改善了细节分布非均匀的模型的简化结果.该方法首先均匀采样,对外存模型快速生成初始简化模型,生成的同时计算原模型特征的统计信息,然后依此对初始简化模型进行细节迁移和局部精细采样.该方法在保持近似线性处理速度的同时,大大提高了简化模型的质量,所需的内存空间也非常小.     

基于视觉原理的多分辨率地形生成准则

目前多分辨率地形的生成准则主要是屏幕空间误差或其变相表达的地形粗糙度,但该类误差准则仅适于对近处的地形进行简化.为了能对远处的地形进行简化,因而从能量传播的角度出发,提出了一个适合对离视点较远的区域进行简化的残余能量准则,同时将其与屏幕空间误差相结合,建立了一个基于视觉原理的多分辨率地形生成准则,并给出了一个基于四叉树结构的实时生成算法.实验表明,该算法能有效减少三角形的数目,并能适合于大规模地形的实时显示应用.     

一遍完成的平衡布点外存模型简化算法

现存的自适应采样的外存模型简化算法均需要多次读取原模型，算法效率较低。该文给出一种仅仅需要读取原模型一遍的自适应顶点聚类算法－平衡布点算法（Balanced Tilling,BT），用于外存模型简化。其关键思想在于通过表面编码记录模型表面，通过对原模型的二次量化（quadric quantization）得到原模型上的细节分布。该算法可以定位出所有类型的细节区域，而其它一些算法只能定位细节边。细节区域将被进一步细化，而平滑区域将被进一步简化。该算法大大减少了输入输出时间，尤其适合处理超大规模模型。内存需求很小，只与输出模型规模有关。     

一种针对复杂曲面的快速自由交互拾取算法

三维模型的交互拾取作为最直观的人机交互方式,在各个领域都有广泛地应用,如几何建模、 3D 游戏和有限元分析等。针对目前含有复杂曲面模型的拾取效率和拾取自由度低等问题,提出了一种对复杂 曲面的快速自由交互拾取算法。首先采用一种类似画刷的工具,对画刷在屏幕中移动的路径进行离散,接着对 每一个离散点应用基于 BVH 结构的单点拾取法来拾取复杂曲面,然后用 2 个哈希结构降低算法的响应时间, 最后对该算法进行了验证。     

Constraint-Based Tiled Windows

Typical computer workstations employ window managers for creating, destroying, and arranging windows on the screen. Window managers generally follow either a desktop metaphor, allowing windows to overlap each other like sheets of paper on a desk, or they use a tiling model, arranging each window with a specific size and location that avoids overlap. Desktop models allow for the most layout freedom, but can be frustrating to use when dealing with a large number of windows that must all be visible at once. Tiling models guarantee that each window will be completely visible on the screen, but thus far have provided relatively poor mechanisms for controlling layout decisions. This article describes work in tiled window management featuring a constraint-based layout mechanism. With it the user can specify the appearance of individual windows and constrain relationships between windows, thus exercising necessary control over the tiling process. We discuss our constraint model and then detail an implementation approach that would make use of those constraints.     

基于法矢调整的浮雕曲面粘贴算法

浮雕是一类将细节附着在平面或曲面背景上的复杂曲面,设计时其背景大多为平面,应用时根据需要将其粘贴在不同的三维产品表面上,这就是浮雕曲面的粘贴问题。将浮雕和目标物体均用三角网格模型表示,提取粘贴的区域作为目标曲面并将其参数化到一个平面上,建立浮雕附着的平面与目标曲面之间的关系,然后设计一种法矢调整算法使得浮雕在目标曲面上变形较小,最后将浮雕和目标曲面合成为一个完整的三角网格。所提算法不仅适合形状变化平缓、曲率小的目标曲面,对于曲率大的目标曲面也有较好的粘贴效果。     

三次B样条插值的网格拼接和融合

目的 网格模型的拼接和融合是3维模型编辑的一个重要方面。为了提高3维模型之间拼接曲面的精度和效率,提出一种基于三次均匀B样条曲线曲面的网格融合方法。方法 首先,利用协变分析和数据驱动方法在目标模型上选定融合区域、确定要融合模型的大小及方向;其次,根据选定的3维网格模型,确定待拼接区域的边界,识别并记录边界点集,利用三次B样条插值边界点集;然后,对边界曲线进行双三次B样条曲面插值得到拼接区域连续曲面,并以此作为两模型拼接时的过渡面;最后,对拼接区域重采样,并对其三角化,以实现网格模型的无缝光滑拼接和融合。结果 为了验证本文方法对3维模型拼接的有效性,选取4组不同的模型,分别对其使用本文提出的融合拼接方法进行实验,对前两组模型的拼接效果进行了对比试验,实验结果表明,本文方法可以达到很好的拼接效果,对于融合区域以外的部分能够保持源模型的细节特征,拼接部分的过渡区域光顺平滑,拼接后的模型完整性佳。在运行时间相差0.05 s内,与数据驱动的建模方法相比,本文方法可以处理的节点数至少多2 000个,面片数至少多5 000个。结论 本文方法能够适用于具有任何边界的模型,在选取模型时,对于模型的形状、大小、拓扑结构等的要求较低,适用于新模型的快速建造,因此,该算法可应用于医学、商业广告、动画娱乐以及几何建模和制造等较为广阔的应用领域。     

自适应分割的动态网格生成算法

提出一种基于半边数据结构的动态网格自适应分割生成算法．根据曲面尖锐特征对网格模型自适应分割;为满足分割边界的简化要求,提出一种利用半边数据结构的分割边界独立处理算法;并利用边界自适应加权函数,较好地保持了模型边界特征．应用实例表明,该算法高效、可靠,既保持模型细节特征,又减少了模型简化误差．     

基于Netgen的层状地质体四面体网格划分方法

为解决三维地质建模中难以表达层状地质体内部属性的问题,将有限元网格划分方法应用于层状地质体建模中,研究基于Netgen进行层状地质体四面体网格划分的方法.以地质钻探数据为数据源,按照钻孔数据分层构建三维表面模型,用三角面片的集合构成封闭的包围壳来描述层状地质体的外部形状;结合Netgen强大的几何自适应和细部划分控制功能,用四面体网格划分方法对形成的三维表面模型进行空间区域划分,从而实现对复杂形状的层状地质体三维模型构建,并分析Netgen的输入、输出数据结构和地质钻探数据到STL格式的三维模型数据、STL格式数据到Netgen网格划分结果数据的生成过程.某矿区多个岩层的模型构建证明该方法稳定、可靠且有效.     

层次隐式张量积B-样条曲面及其在曲面重构中的应用

提出一类新的隐式曲面表示形式,它具有良好的层次性与自适应性,特别适合于表示层次细节模型.首先给出层次隐式张量积B-样条曲面的定义,回顾曲面重构的一般数学模型,然后提出适于求解该类曲面的最优化模型以及定义域自适应分解的方法.在此基础之上,提出层次逼近算法来逼近采样点数据集.随后,引入单位分解方法,将其用于融合各个子域上的局部逼近函数,使其成为一个具有整体光滑性的函数.最后基于散乱点数据集,给出曲面重构的实例,并作简单的讨论.     

基于轻量化重构网络的表面缺陷视觉检测

基于深度学习的方法在某些工业产品的表面缺陷识别和分类方面表现出优异的性能,然而大多数工业产品缺陷样本稀缺,而且特征差异大,导致这类需要大量缺陷样本训练的检测方法难以适用.提出一种基于重构网络的无监督缺陷检测算法,仅使用容易大量获得的无缺陷样本数据实现对异常缺陷的检测.提出的算法包括两个阶段:图像重构网络训练阶段和表面缺陷区域检测阶段.训练阶段通过一种轻量化结构的全卷积自编码器设计重构网络,仅使用少量正常样本进行训练,使得重构网络能够生成无缺陷重构图像,进一步提出一种结合结构性损失和L1损失的函数作为重构网络的损失函数,解决自编码器检测算法对不规则纹理表面缺陷检测效果较差的问题;缺陷检测阶段以重构图像与待测图像的残差作为缺陷的可能区域,通过常规图像操作即可实现缺陷的定位.对所提出的重构网络的无监督缺陷检测算法的网络结构、训练像素块大小、损失函数系数等影响因素进行了详细的实验分析,并在多个缺陷图像样本集上与其他同类算法做了对比,结果表明重构网络的无监督缺陷检测算法有较强的鲁棒性和准确性.由于重构网络的无监督缺陷检测算法的轻量化结构,检测1 024×1 024像素图像仅仅耗时2.82 ms,...     

面向球幕投影系统的几何校正方法

摘 要：用于飞行模拟的视景仿真系统，经常会以多台投影仪同步投影以得到较大范围的 视场角。当投影机斜对屏幕或者投影屏幕为曲面时，图像会发生几何失真。针对此问题，本文 提出了一种专门面向球幕投影系统的几何校正方法，并以一个三通道显示系统为实例，详述了 该方法的理论原理以及校正流程。实例结果表明，经几何校正后，各投影图像无几何畸变，通 道过渡处几何内容完全一致。该方法是一种纯软件方法，成本小而且操作简单，能够适应于不 同的投影场景。     

基于分布式操作系统的三维城市模型组织方法

日益增长的三维城市模型在线实时可视化应用需求对大规模复杂三维城市模型的高效组织与管理提出了更高的要求,传统基于"图层-对象"的组织方法没有考虑三维城市模型不同内容以及不同细节层次的粒度差异,导致在网络环境下的传输效率很低,难以满足网络环境下多用户并发访问的流畅可视化需求。本文深入分析大范围漫游与小范围聚焦的不同用户体验特点,提出了顾及用户体验的面向网络实时可视化的复杂三维城市模型数据自适应组织方法。该方法采用索引元数据统筹模型对象的组织与调度,将小数据量的索引元数据和最粗一级模型数据打包传输,即时响应用户请求,并将多细节层次的复杂三维模型依据视觉特点合理分解存储并渐进调度,针对模型LOD和分解的对象,设计结构统一的对象ID,隐式存储关联关系并支持分布式模型存储管理。以分布式数据MongoDB为平台进行实验,验证了本文方法的可行性和有效性。     

图形处理器上地质模型的快速体素化

基于图形处理器(GPU)上的多目标缓存提出了一种新的地质模型快速体素化算法,可以在GPU上绘制模型的过程中在像素着色器中利用多目标缓存上的逻辑或操作完成模型表面体素化处理,在后处理的屏幕绘制过程中对模型内部进行体素化填充,极大地提高了计算速度,使得大规模地质模型可以在常见GPU平台上得以实时体素化,可以较好地处理模型内部的空腔等问题。针对算法在模型相近表面或微小凹凸处会产生错误的情况,设计了一种基于逻辑异或操作的实体体素化改进算法,使其结果更为快速准确。     

利用视频存储器实现屏幕图像暂存与恢复

本文介绍了如何利用VGA视频存储器（VRAM）的剩余空间来快速保存和恢复屏幕上的一个矩形区域的方法。     

基于深度前馈神经网络的多因子人体表面积计算模型

人体表面积(BSA)在临床医学上有着至关重要的作用,但现有BSA计算方法大多只使用身高和体重2个参数且采用匹配简单函数的方法来估计体表面积,临床上也认为现有的BSA计算方法误差较大。针对这些问题,提出一种BSA回归预测模型。该回归预测模型包含2个部分：首先,借助相关性和显著性分析选择相关性较高的体表面积影响因子;其次,利用人体数据训练深度前馈神经网络,构建回归模型。实验分别采取5-折交叉验证与测试集验证2种方法。首先,将深度前馈神经网络模型与传统人体表面积计算方法进行精度评估和结果对比分析;其次将深度前馈神经网络模型与3种模型进行精度评估和结果对比分析。在与传统方法对比中,深度前馈神经网络模型的决定系数高于2种传统方法的,且比传统方法提高了6%,误差与传统方法的相比降低了近一倍。在与3种模型的对比中,深度前馈神经网络的决定系数比其他模型的提高了至少2%,误差降低。一致性分析实验结果也显示,深度前馈神经网络95%一致性界限最小,一致性最好。总体来说,提出的回归预测模型可以得到更加精确的体表面积预测值。     

Interactive modeling of complex geometric details based on empirical mode decomposition for multi-scale 3D shapes

In this paper we develop an interactive modeling system for complex geometric details transformation based on empirical mode decomposition (EMD) on multi-scale 3D shapes. Given two models, we aim to transfer geometric details from one model to another one in an interactive manner. Taking full advantages of the multi-scale representation computed via EMD, different-scale geometric details can be transferred individually or in a concerted way, which makes our algorithm much more flexible than cut-and-paste and cloning based methods in transferring geometry details. In this process, the target surface with new transferred details could be generated by a mesh reconstruction method widely used in Laplacian surface editing. With the original positions of target surface serving as the soft constraints, the overall shape of the target model will be fully preserved. Our method can also support real-time continuous details transfer. Compared with state-of-the-art algorithms, our method provides an easier-to-use modeling tool and produces varied modeling results. We demonstrate the effectiveness of our modeling tool with various applications, such as detail transfer and enrichment, model reuse and recreation, and detail recovery for shape completion.     

Estimating surface air temperatures,from Meteosat land surface temperatures,using an empirical solar zenith angle model

Temperature values derived from Meteosat are an indication of emitted long-wave radiation, and are not a true indication of ambient air temperature. The authors believe that Solar Zenith Angle (SZA) can be used as a proxy for solar energy reaching the ground surface, and its subsequent effects upon the land surface temperature detected by Meteosat. Raw satellite temperatures often overestimate the actual screen temperature during the day, and underestimate at night. By using a statistical model which relates Meteosat and WMO screen temperature deviations, and SZA values, it has been possible to generate a correction algorithm which minimizes these differences. The algorithm generates a new proxy value, being a simulated ambient (screen) air temperature. The algorithms achieve an accuracy of within 3 C for over 70% of the Meteosat temperatures processed. The operational use of this algorithm requires only the raw Meteosat temperature value, and the SZA. Such temperature corrections are useful for a wide range of environmental monitoring applications. An example is in the field of vector-borne disease modelling which requires proxies for temperature across large regions, and where more conventional meteorological stations are inadequate.