增强型IBFV 2维矢量场可视化算法

提出一种基于质点平流的增强型IBFV可视化算法,可显著增加IBFV算法生成图像的对比度。首先通过质点平流获得一系列的矢量纹理;然后将这些矢量纹理作为IBFV算法中的背景图像,代替原来的噪声纹理与帧缓存中的纹理进行图像混合生成新图。通过这种方式不仅可以准确反映流场的动态变化,而且增强了矢量线间的对比,同时还可以获得较高的绘制速度。     

飞行器表面矢量场数据动态纹理可视化方法

面向飞行器表面流场数据可视化的应用需求,提出一种基于线性卷积（LIC）及纹理平流（IBFVS）相结合的动态纹理可视化方法。算法通过将IBFVS方法的背景随机噪声替换为LIC纹理方式,结合了LIC纹理结果对比度高及IBFVS方法生成速度快的优势;针对LIC绘制速度慢的不足,利用GPU对曲面矢量场投影并插值,生成规则矢量数据场;用GPU对LIC部分进行并行加速,有效提高了LIC纹理图像产生速度;将LIC结果图像加入到IBFVS进行平流,生成纹理图像,最后加入颜色映射,丰富流场信息。实验结果表明,该方法生成的飞行器表面动态纹理图像对比度高,清晰度强,实时绘制性能好。     

基于信息熵的流场定向线积分卷积算法

流场可视化是对流场数据进行直观分析的一种新的可视化技术,而定向线积分卷积（OLIC）算法作为一种经典的纹理可视化方法,使用该算法能明显地观察出流场方向流动的演化。为了优化可视化效果,提出了一种基于信息熵的OLIC算法。首先,基于流场矢量数据生成基于信息熵的稀疏噪声;然后,采用斜坡卷积核函数对输入纹理进行卷积计算;最后,通过计算输出纹理图像中每一个像素点的灰度值,得到最终的OLIC纹理图像。所提算法可以根据熵值在临界点区域和非临界点区域自适应地生成流线。其中临界点区域含有流场的重要信息,选择密集绘制;而在非临界点区域则选择稀疏绘制。通过在不同区域绘制不同密度的流线,所提算法节省了计算成本;与普通OLIC算法相比,所提算法的绘制速度至少提升了18.6%;在可视化效果方面,所提算法优于普通的全局绘制,使用所提算法能更仔细地观察特征区域。     

基于粒子纹理融合的流场可视化方法

基于纹理的可视化方法可以描述流场的整体结构,但传统方法计算耗时,生成可视化图像对比度比较低。从加速可视化整体流程出发,提出了一种基于粒子纹理融合的流场可视化方法。此方法首先随机产生一组噪声图像作为初始粒子分布图,然后依次将初始粒子分布图与根据流动而变形的数据网格加权融合得到粒子轨迹图,最后一帧帧彼此相邻的粒子轨迹图组成一个流场的动态显示。该方法具有独立于流场数据、绘制速度快、生成图像对比度高的特点,参数物理意义明显,不同参数选择可得到不同视觉效果的可视化输出结果,能够充分利用现有硬件图形显示加速设备,已经被成功应用于空间晶体生长实验流场数据的可视化,获得了较好的效果。     

基于半规则纹理合成的流场可视化技术

直接利用半规则纹理本身蕴涵的方向信息对流场进行可视化．结果直观有效,而且适用的纹理范围广泛,丰富了流场可视化的手段,首先应用基于块的二维方向纹理合成方法生成第一帧图像,随着流体的流动,每一小块的4个顶点移动到新的位置,然后将原有的纹理映射到新的四边形上,同时计算出每个点的变形程度,如果某点变形过大,那么把该点标为无效点,重新合成,最后,一帧帧连续合成的纹理组成一个流场可视化的动画。     

一种新的VolumeLIC可视化方法

矢量场可视化是科学计算可视化中最具挑战性的研究课题之一,为了能在二维屏上直观显示三维矢量场,将基于纹理的LIC方法拓展到三维矢量场可视化,通过设计稀疏线噪声纹理并配合斜坡卷积核提高VolumeLIC图象质量,显著增强空间深度感,并采用光线投射直接体绘制方法生成VolumeLIC图象,另外,针对循环动画的突兀现象,提出HRCK（Hanninged RampConvolutionKernel)法生成流场的VolumeLIC循环动画,提出VolumeLICProbe交互洞察三维矢量场内部信息,通过实例表明,本文所提方法具有良好的可视化效果,交互方便,并已应用地幔可视化等领域。     

基于时空一致性的非结构化网格时变流场高效体绘制方法

时空一致性是时变流场的重要性质,也是加速时变数据可视化算法的关键.以硬件加速的光线投射算法(HRC)为框架,设计并实现了一种基于时空一致性的非结构化网格时变流场高效体绘制方法.首先提出一种分析非结构化网格单元和顶点数据时间一致性的方法,分别建立单元和顶点数据时间表,以降低绘制过程中的计算开销;然后设计一种单元和顶点数据相分离的GPU纹理结构,并采用一种小巧的单元梯度矩阵来降低显存开销;同时,设计了一种合理的数据调度策略,既能有效地避免绘制停顿,又使显存纹理结构更为紧致、高效.实验结果表明,该方法不仅明显地提高了绘制效率,而且具有更优显存空间利用率,能实现更大网格规模的非结构化网格时变流场数据体绘制.     

基于GPU加速的3D矢量场改进VolumeLIC绘制技术

纹理绘制技术通过纹理线条和颜色变化能够细致且生动地表现2D矢量场的速度、方向以及数据相关性等特征信息,但扩展到3D矢量场空间时,由于3D矢量场本身的空间特性容易造成纹理单元之间产生严重的视线遮挡问题,影响研究人员对矢量场内部固有属性特征的观察和分析.针对此问题,提出一种基于GPU加速实现的稀疏噪声纹理生成的改进3D矢量场Volume LIC绘制技术.在噪声生成部分,基于泊松盘分布以避免噪声点间的相互遮挡,采用Hilbert空间填充线遍历减少生成噪声点的规律性和人工痕迹,并通过高斯滤波核滤除高频区域生成稀疏高斯噪声.整个算法采用GPU+GLSL硬件加速机制,在噪声纹理采样时,利用GPU顶点颜色线性插值功能和片元计算方法有效地加速LIC纹理生成过程,并将卷积噪声和矢量场数据作为纹理传入GPU;采用光线投射算法实现LIC纹理的3D绘制显示,并通过光线提前终止技术和空白空间跳跃技术有效提升绘制效率;同时提供多种有效的交互分析手段查看流场内部特征.实验结果表明,该方法生成的3D纹理图像清晰、绘制效率高,能够有效地缓解3D复杂矢量场卷积数据过多引起的遮挡与混乱现象,具备良好的可视化效果.     

一种基于图像相位变化的动画算法

W.T.Freeman等人提出了基于图像相位变化的动画算法。该文利用这种动画算法,结合光流场,在一个动画或视频的连续两帧图像之间实现了永不停止的动画。在灰度图像上实现这种动画的基础上,针对这种无移动动画对图像质量的损害,进行了灰度拉伸等后期处理,提高了动画的图像质量。另外,把这种算法扩展到彩色图像,并采用lαβ颜色空间,得到了更好的效果。最后,把这种动画通过纹理映射,应用到三维场景中。     

增强纹理平流算法研究

当以纹理方式可视化三维矢量场时,纹理卷积会降低矢量纹理脉的对比度,容易出现平流纹理细节模糊与粗糙的问题,为此提出一种增强纹理平流算法.首先通过自定义球体半径确定任一噪声点的邻近点,利用当前噪声点与邻近点间的位置关系计算噪声伪梯度,以测试矢量场局部区域内的变化趋势,选取伪梯度的最大下降幅度参与纹理平流;然后根据任一平流位置处的噪声值对最终输出纹理的贡献度自适应调整噪声权重;最后引入盒型滤波递归合成平滑算子进行纹理卷积来生成矢量体纹理.算法的有效性根据可视化对比度的量化分析函数进行客观评价.实验结果表明,该算法能够有效地增加纹理平流踪迹间强度对比,改善绘制效果,高质量地显示三维矢量场的纹理分布.     

Lagrangian-Eulerian advection of noise and dye textures for unsteady flow visualization

A new hybrid scheme, called Lagrangian-Eulerian advection (LEA), that combines the advantages of the Eulerian and Lagrangian frameworks is applied to the visualization of dense representations of time-dependent vector fields. The algorithm encodes the particles into a texture that is then advected. By treating every particle equally, we can handle texture advection and dye advection within a single framework. High temporal and spatial correlation is achieved through the blending of successive frames. A combination of particle and dye advection enables the simultaneous visualization of streamlines, particle paths and streak-lines. We demonstrate various experimental techniques on several physical flow fields. The simplicity of both the resulting data structures and the implementation suggest that LEA could become a useful component of any scientific visualization toolkit concerned with the display of unsteady flows.     

Efficient level of detail for texture‐based flow visualization

In this paper, we present an efficient level of detail algorithm for texture‐based flow visualization. Our goal is to enhance visual perception and performance and generate smooth animation. To achieve our goal, we first model an adaptive input texture taking into account flow patterns to output view‐dependent high‐quality images. Then, we compute field lines only from sparse sampling points of the input noise texture for outputting volume line integral convolution textures and skip empty space utilizing two quantized binary histograms. To improve image quality, we implement anti‐aliasing through adjusting the line integral convolution step size and thickness of trajectory lines with an opacity function. We further extend our solution to unsteady flow. Flow structures and evolution are clearly shown through smooth animation achieved with coherent evolution of particles, handling of discontinuous flow lines, and spatio‐temporal linear constraint of the underlying noise volume. In the result section, we show high‐quality level of detail of three‐dimensional texture‐based flow visualization with high performance. We also demonstrate that our algorithm can achieve smooth evolution for unsteady flow with spatio‐temporal coherence. Copyright © 2015 John Wiley & Sons, Ltd.     

Accelerated unsteady flow line integral convolution

Unsteady flow line integral convolution (UFLIC) is a texture synthesis technique for visualizing unsteady flows with high temporal-spatial coherence. Unfortunately, UFLIC requires considerable time to generate each frame due to the huge amount of pathline integration that is computed for particle value scattering. This paper presents accelerated UFLIC (AUFLIC) for near interactive (1 frame/second) visualization with 160,000 particles per frame. AUFLIC reuses pathlines in the value scattering process to reduce computationally expensive pathline integration. A flow-driven seeding strategy is employed to distribute seeds such that only a few of them need pathline integration while most seeds are placed along the pathlines advected at earlier times by other seeds upstream and, therefore, the known pathlines can be reused for fast value scattering. To maintain a dense scattering coverage to convey high temporal-spatial coherence while keeping the expense of pathline integration low, a dynamic seeding controller is designed to decide whether to advect, copy, or reuse a pathline. At a negligible memory cost, AUFLIC is 9 times faster than UFLIC with comparable image quality     

High-quality and interactive animations of 3D time-varying vector fields

In this paper, we present an interactive texture-based method for visualizing three-dimensional unsteady vector fields. The visualization method uses a sparse and global representation of the flow, such that it does not suffer from the same perceptual issues as is the case for visualizing dense representations. The animation is made by injecting a collection of particles evenly distributed throughout the physical domain. These particles are then tracked along their path lines. At each time step, these particles are used as seed points to generate field lines using any vector field such as the velocity field or vorticity field. In this way, the animation shows the advection of particles while each frame in the animation shows the instantaneous vector field. In order to maintain a coherent particle density and to avoid clustering as time passes, we have developed a novel particle advection strategy which produces approximately evenly-spaced field lines at each time step. To improve rendering performance, we decouple the rendering stage from the preceding stages of the visualization method. This allows interactive exploration of multiple fields simultaneously, which sets the stage for a more complete analysis of the flow field. The final display is rendered using texture-based direct volume rendering     

A new line integral convolution algorithm for visualizingtime-varying flow fields

New challenges on vector field visualization emerge as time dependent numerical simulations become ubiquitous in the field of computational fluid dynamics (CFD). To visualize data generated from these simulations, traditional techniques, such as displaying particle traces, can only reveal flow phenomena in preselected local regions and thus, are unable to track the evolution of global flow features over time. The paper presents an algorithm, called UFLIC (Unsteady Flow LIC), to visualize vector data in unsteady flow fields. Our algorithm extends a texture synthesis technique, called Line Integral Convolution (LIC), by devising a new convolution algorithm that uses a time-accurate value scattering scheme to model the texture advection. In addition, our algorithm maintains the coherence of the flow animation by successively updating the convolution results over time. Furthermore, we propose a parallel UFLIC algorithm that can achieve high load balancing for multiprocessor computers with shared memory architecture. We demonstrate the effectiveness of our new algorithm by presenting image snapshots from several CFD case studies     

Unsteady Flow Visualization by Animating Evenly-Spaced Streamlines

In recent years the work on vector field visualization has been concentrated on LIC-based methods. In this paper we propose an alternative solution for the visualization of unsteady flow fields. Our approach is based on the computation of temporal series of correlated images. While other methods are based on pathlines and try to correlate successive images at the pixel level, our approach consists in correlating instantaneous visualizations of the vector field at the streamline level. For each frame a feed forward algorithm computes a set of evenly-spaced streamlines as a function of the streamlines generated for the previous frame. This is achieved by establishing a correspondence between streamlines at successive time steps. A cyclical texture is mapped onto every streamline and textures of corresponding streamlines at different time steps are correlated together so that, during the animation, they move along the streamlines, giving the illusion that the flow is moving in the direction defined by the streamline. Our method gives full control on the image density so that we are able to produce smooth animations of arbitrary density, covering the field of representations from sparse, that is classical streamline-based images, to dense, that is texture-like images.     

Fast example-based surface texture synthesis via discrete optimization

We synthesize and animate general texture patterns over arbitrary 3D mesh surfaces. The animation is controlled by flow fields over the target mesh, and the texture can be arbitrary user input as long it satisfies the Markov-Random-Field assumptions. We achieve this by extending the texture optimization framework over 3D mesh surfaces. We propose an efficient discrete solver inspired by k-coherence search, allowing interactive flow texture animation while avoiding the blurry blending problem for the least square solver in previous work. Our technique has potential applications ranging from simulation, visualization, and special effects.     

ISA and IBFVS: image space-based visualization of flow on surfaces

We present a side-by-side analysis of two recent image space approaches for the visualization of vector fields on surfaces. The two methods, image space advection (ISA) and image-based flow visualization for curved surfaces (IBFVS) generate dense representations of time-dependent vector fields with high spatio-temporal correlation. While the 3D vector fields are associated with arbitrary surfaces represented by triangular meshes, the generation and advection of texture properties is confined to image space. Fast frame rates are achieved by exploiting frame-to-frame coherency and graphics hardware. In our comparison of ISA and IBFVS, we point out the strengths and weaknesses of each approach and give recommendations as to when and where they are best applied.