A single-pass GPU ray casting framework for interactive out-of-core rendering of massive volumetric datasets

We present an adaptive out-of-core technique for rendering massive scalar volumes employing single-pass GPU ray casting. The method is based on the decomposition of a volumetric dataset into small cubical bricks, which are then organized into an octree structure maintained out-of-core. The octree contains the original data at the leaves, and a filtered representation of children at inner nodes. At runtime an adaptive loader, executing on the CPU, updates a view and transfer function-dependent working set of bricks maintained on GPU memory by asynchronously fetching data from the out-of-core octree representation. At each frame, a compact indexing structure, which spatially organizes the current working set into an octree hierarchy, is encoded in a small texture. This data structure is then exploited by an efficient stackless ray casting algorithm, which computes the volume rendering integral by visiting non-empty bricks in front-to-back order and adapting sampling density to brick resolution. Block visibility information is fed back to the loader to avoid refinement and data loading of occluded zones. The resulting method is able to interactively explore multi-gigavoxel datasets on a desktop PC.     

Incremental Volume Rendering Using Hierarchical Compression

We present a new algorithm here for efficient incremental rendering of volumetric datasets. The primary goal of this algorithm is to give average workstations the ability to efficiently render volume data received over relatively low bandwidth network links in such a way that rapid user feedback is maintained. Common limitations of workstation rendering of volume data include: large memory overheads, the requirement of expensive rendering hardware, and high speed processing ability. The rendering algorithm presented here overcomes these problems by making use of the efficient Shear-Warp Factorisation method which does not require specialised graphics hardware. However the original Shear-Warp algorithm suffers from a high memory overhead and does not provide for incremental rendering which is required should rapid user feedback be maintained. Our algorithm represents the volumetric data using a hierarchical data structure which provides for the incremental classification and rendering of volume data. This exploits the multiscale nature of the octree data structure. The algorithm reduces the memory footprint of the original Shear-Warp Factorisation algorithm by a factor of more than two, while maintaining good rendering performance. These factors make our octree algorithm more suitable for implementation on average desktop workstations for the purposes of interactive exploration of volume models over a network. Results from tests using typical volume datasets will be presented which demonstrate the ability of the algorithm to achieve high rendering rates for both incremental rendering and standard rendering while reducing the runtime memory requirements.     

Direct Visualization of Deformation in Volumes

Deformation is a topic of interest in many disciplines. In particular in medical research, deformations of surfaces and even entire volumetric structures are of interest. Clear visualization of such deformations can lead to important insight into growth processes and progression of disease.
We present new techniques for direct focus+context visualization of deformation fields representing transformations between pairs of volumetric datasets. Typically, such fields are computed by performing a non-rigid registration between two data volumes. Our visualization is based on direct volume rendering and uses the GPU to compute and interactively visualize features of these deformation fields in real-time. We integrate visualization of the deformation field with visualization of the scalar volume affected by the deformations. Furthermore, we present a novel use of texturing in volume rendered visualizations to show additional properties of the vector field on surfaces in the volume.     

Multiresolution volume visualization with a texture-based octree

Although 3D texture-based volume rendering guarantees image quality almost interactively, it is difficult to maintain an interactive rate when the technique has to be exploited on large datasets. In this paper, we propose a new texture memory representation and a management policy that substitute the classical one-texel per voxel approach for a hierarchical approach. The hierarchical approach benefits nearly homogeneous regions and regions of lower interest. The proposed algorithm is based on a simple traversal of the octree representation of the volume data. Driven by a user-defined image quality, defined as a combination of data homogeneity and importance, a set of octree nodes (the cut) is selected to be rendered. The degree of accuracy applied for the representation of each one of the nodes of the cut in the texture memory is set independently according to the user-defined parameters. The variable resolution texture model obtained reduces the texture memory size and thus texture swapping, improving rendering speed.     

Interactive multiscale tensor reconstruction for multiresolution volume visualization

Large scale and structurally complex volume datasets from high-resolution 3D imaging devices or computational simulations pose a number of technical challenges for interactive visual analysis. In this paper, we present the first integration of a multiscale volume representation based on tensor approximation within a GPU-accelerated out-of-core multiresolution rendering framework. Specific contributions include (a) a hierarchical brick-tensor decomposition approach for pre-processing large volume data, (b) a GPU accelerated tensor reconstruction implementation exploiting CUDA capabilities, and (c) an effective tensor-specific quantization strategy for reducing data transfer bandwidth and out-of-core memory footprint. Our multiscale representation allows for the extraction, analysis and display of structural features at variable spatial scales, while adaptive level-of-detail rendering methods make it possible to interactively explore large datasets within a constrained memory footprint. The quality and performance of our prototype system is evaluated on large structurally complex datasets, including gigabyte-sized micro-tomographic volumes.     

Volumetric Billboards

We introduce an image‐based representation, called volumetric billboards, allowing for the real‐time rendering of semi‐transparent and visually complex objects arbitrarily distributed in a 3D scene. Our representation offers full parallax effect from any viewing direction and improved anti‐aliasing of distant objects. It correctly handles transparency between multiple and possibly overlapping objects without requiring any primitive sorting. Furthermore, volumetric billboards can be easily integrated into common rasterization‐based renderers, which allows for their concurrent use with polygonal models and standard rendering techniques such as shadow‐mapping. The representation is based on volumetric images of the objects and on a dedicated real‐time volume rendering algorithm that takes advantage of the GPU geometry shader. Our examples demonstrate the applicability of the method in many cases including levels‐of‐detail representation for multiple intersecting complex objects, volumetric textures, animated objects and construction of high‐resolution objects by assembling instances of low‐resolution volumetric billboards.     

Interactive fragment tracing

One of the main challenges in real-time rendering is to enable more and more effects that were previously available in offline rendering only. An important effect among these is physically correct reflections of arbitrary objects in curved reflectors like windshields. In this paper we propose fragment tracing on the GPU as a solution to interactively realizing this effect for large scenes as employed in industrial applications. For each rasterized fragment, a ray is traced through an octree representing the original geometry and surface material. By introducing a GPU implementation of an octree traversal, for the first time hierarchical data structures can efficiently be used on the GPU. As a result, the approach allows both handling of large geometries such as those employed in virtual prototyping and accurate rendering. Several examples show the generality and achievable rendering quality of our method.     

Fast Volume Rendering and Data Classification Using Multiresolution in Min‐Max Octrees

Large‐sized volume datasets have recently become commonplace and users are now demanding that volume‐rendering techniques to visualise such data provide acceptable results on relatively modest computing platforms. The widespread use of the Internet for the transmission and/or rendering of volume data is also exerting increasing demands on software providers. Multiresolution can address these issues in an elegant way. One of the fastest volume‐rendering alrogithms is that proposed by Lacroute & Levoy ¹ , which is based on shear‐warp factorisation and min‐max octrees (MMOs). Unfortunately, since an MMO captures only a single resolution of a volume dataset, this method is unsuitable for rendering datasets in a multiresolution form. This paper adapts the above algorithm to multiresolution volume rendering to enable near‐real‐time interaction to take place on a standard PC. It also permits the user to modify classification functions and/or resolution during rendering with no significant loss of rendering speed. A newly‐developed data structure based on the MMO is employed, the multiresolution min‐max octree, M ³ O, which captures the spatial coherence for datasets at all resolutions. Speed is enhanced by the use of multiresolution opacity transfer functions for rapidly determining and discarding transparent dataset regions. Some experimental results on sample volume datasets are presented.     

Interactive isosurface ray tracing of time-varying tetrahedral volumes

We describe a system for interactively rendering isosurfaces of tetrahedral finite-element scalar fields using coherent ray tracing techniques on the CPU. By employing state-of-the art methods in polygonal ray tracing, namely aggressive packet/frustum traversal of a bounding volume hierarchy, we can accomodate large and time-varying unstructured data. In conjunction with this efficiency structure, we introduce a novel technique for intersecting ray packets with tetrahedral primitives. Ray tracing is flexible, allowing for dynamic changes in isovalue and time step, visualization of multiple isosurfaces, shadows, and depth-peeling transparency effects. The resulting system offers the intuitive simplicity of isosurfacing, guaranteed-correct visual results, and ultimately a scalable, dynamic and consistently interactive solution for visualizing unstructured volumes.     

LOCALIS: Locally-adaptive Line Simplification for GPU-based Geographic Vector Data Visualization

Visualization of large vector line data is a core task in geographic and cartographic systems. Vector maps are often displayed at different cartographic generalization levels, traditionally by using several discrete levels-of-detail (LODs). This limits the generalization levels to a fixed and predefined set of LODs, and generally does not support smooth LOD transitions. However, fast GPUs and novel line rendering techniques can be exploited to integrate dynamic vector map LOD management into GPU-based algorithms for locally-adaptive line simplification and real-time rendering. We propose a new technique that interactively visualizes large line vector datasets at variable LODs. It is based on the Douglas-Peucker line simplification principle, generating an exhaustive set of line segments whose specific subsets represent the lines at any variable LOD. At run time, an appropriate and view-dependent error metric supports screen-space adaptive LOD levels and the display of the correct subset of line segments accordingly. Our implementation shows that we can simplify and display large line datasets interactively. We can successfully apply line style patterns, dynamic LOD selection lenses, and anti-aliasing techniques to our line rendering.     

Visibility-Aware Direct Volume Rendering

Direct volume rendering (DVR) is a powerful visualization technique which allows users to effectively explore and study volumetric datasets.Different transparency settings can be flexibly assigned to different structures such that some valuable information can be revealed in direct volume rendered images (DVRIs).However,end-users often feel that some risks are always associated with DVR because they do not know whether any important information is missing from the transparent regions of DVRIs.In this paper,we investigate how to semi-automatically generate a set of DVRIs and also an animation which can reveal information missed in the original DVRIs and meanwhile satisfy some image quality criteria such as coherence.A complete framework is developed to tackle various problems related to the generation and quality evaluation of visibility-aware DVRIs and animations.Our technique can reduce the risk of using direct volume rendering and thus boost the confidence of users in volume rendering systems.     

Octree generation from object silhouettes in perspective views

Octrees are useful for object representation when fast access to coarse spatial occupancy information is necessary. This paper presents an efficient algorithm for generating octrees from multiple perspective views of an object. The algorithm first obtains a polygonal approximation of the object silhouette. This polygon is then decomposed into convex components. For each convex component, a pyramid is formed treating the view point as its apex and the convex components as a cross section. The octree representation of each of these pyramids is obtained by performing intersection detection of the object with the cubes corresponding to octree nodes. The intersection detection step is made efficient by decomposing it into a coarse-to-fine sequence of intersection tests. The octree for one silhouette is obtained by taking the union of octrees obtained for each component. An intersection of octrees corresponding to different viewing directions gives the final octree of the object. An implementation of the algorithm is given. The accuracy of the octree representation of the objects is evaluated. The ratio of the actual volume of the object to the volume of the object reconstructed from the octree representation is used as a performance index of the algorithm.     

CPU Ray Tracing of Tree-Based Adaptive Mesh Refinement Data

Adaptive mesh refinement (AMR) techniques allow for representing a simulation's computation domain in an adaptive fashion. Although these techniques have found widespread adoption in high-performance computing simulations, visualizing their data output interactively and without cracks or artifacts remains challenging. In this paper, we present an efficient solution for direct volume rendering and hybrid implicit isosurface ray tracing of tree-based AMR (TB-AMR) data. We propose a novel reconstruction strategy, Generalized Trilinear Interpolation (GTI), to interpolate across AMR level boundaries without cracks or discontinuities in the surface normal. We employ a general sparse octree structure supporting a wide range of AMR data, and use it to accelerate volume rendering, hybrid implicit isosurface rendering and value queries. We demonstrate that our approach achieves artifact-free isosurface and volume rendering and provides higher quality output images compared to existing methods at interactive rendering rates.     

Error-controlled real-time cut updates for multi-resolution volume rendering

Multi-resolution techniques are required for rendering large volumetric datasets exceeding the size of the graphics card's memory or even the main memory. The cut through the multi-resolution volume representation is defined by selection criteria based on error metrics. For GPU-based volume rendering, this cut has to fit into the graphics card's memory and needs to be continuously updated due to the interaction with the volume such as changing the area of interest, the transfer function or the viewpoint. We introduce a greedy cut update algorithm based on split-and-collapse operations for updating the cut on a frame-to-frame basis. This approach is guided by a global data-based metric based on the distortion of classified voxel data, and it takes into account a limited download budget for transferring data from main memory into the graphics card to avoid large frame rate variations. Our out-of-core support for handling very large volumes also makes use of split-and-collapse operations to generate an extended cut in the main memory. Finally, we introduce an optimal polynomial-time cut update algorithm, which maximizes the error reduction between consecutive frames. This algorithm is used to verify how close to the optimum our greedy split-and-collapse algorithm performs.     

Interactive Volume Rendering with Dynamic Ambient Occlusion and Color Bleeding

We propose a method for rendering volumetric data sets at interactive frame rates while supporting dynamic ambient occlusion as well as an approximation to color bleeding. In contrast to ambient occlusion approaches for polygonal data, techniques for volumetric data sets have to face additional challenges, since by changing rendering parameters, such as the transfer function or the thresholding, the structure of the data set and thus the light interactions may vary drastically. Therefore, during a preprocessing step which is independent of the rendering parameters we capture light interactions for all combinations of structures extractable from a volumetric data set. In order to compute the light interactions between the different structures, we combine this preprocessed information during rendering based on the rendering parameters defined interactively by the user. Thus our method supports interactive exploration of a volumetric data set but still gives the user control over the most important rendering parameters. For instance, if the user alters the transfer function to extract different structures from a volumetric data set the light interactions between the extracted structures are captured in the rendering while still allowing interactive frame rates. Compared to known local illumination models for volume rendering our method does not introduce any substantial rendering overhead and can be integrated easily into existing volume rendering applications. In this paper we will explain our approach, discuss the implications for interactive volume rendering and present the achieved results.     

Direct volume rendering of unstructured tetrahedral meshes using CUDA and OpenMP

Direct volume visualization is an important method in many areas, including computational fluid dynamics and medicine. Achieving interactive rates for direct volume rendering of large unstructured volumetric grids is a challenging problem, but parallelizing direct volume rendering algorithms can help achieve this goal. Using Compute Unified Device Architecture (CUDA), we propose a GPU-based volume rendering algorithm that itself is based on a cell projection-based ray-casting algorithm designed for CPU implementations. We also propose a multicore parallelized version of the cell-projection algorithm using OpenMP. In both algorithms, we favor image quality over rendering speed. Our algorithm has a low memory footprint, allowing us to render large datasets. Our algorithm supports progressive rendering. We compared the GPU implementation with the serial and multicore implementations. We observed significant speed-ups that, together with progressive rendering, enables reaching interactive rates for large datasets.     

Extensions of parallel coordinates for interactive exploration of large multi-timepoint data sets

Parallel coordinate plots (PCPs) are commonly used in information visualization to provide insight into multi-variate data. These plots help to spot correlations between variables. PCPs have been successfully applied to unstructured datasets up to a few millions of points. In this paper, we present techniques to enhance the usability of PCPs for the exploration of large, multi-timepoint volumetric data sets, containing tens of millions of points per timestep. The main difficulties that arise when applying PCPs to large numbers of data points are visual clutter and slow performance, making interactive exploration infeasible. Moreover, the spatial context of the volumetric data is usually lost. We describe techniques for preprocessing using data quantization and compression, and for fast GPU-based rendering of PCPs using joint density distributions for each pair of consecutive variables, resulting in a smooth, continuous visualization. Also, fast brushing techniques are proposed for interactive data selection in multiple linked views, including a 3D spatial volume view. These techniques have been successfully applied to three large data sets: Hurricane Isabel (Vis'04 contest), the ionization front instability data set (Vis'08 design contest), and data from a large-eddy simulation of cumulus clouds. With these data, we show how PCPs can be extended to successfully visualize and interactively explore multi-timepoint volumetric datasets with an order of magnitude more data points.     

基于满二叉树分块策略的大规模数据场纹理映射体绘制算法

针对纹理映射体绘制物理内存空间的限制,本文提出一种可在通用图形硬件上完成大规模数据场实时体绘制的有效方法.该方法基于满二叉树纹理分块策略,利用GPU着色器可编程性,将纹理数据制作为一个一维传递函数查找表和一个规模等同于体数据场的动态纹理工作集,有效提高了大规模数据场体绘制的实时性.动态纹理工作集使用抽象分块与继承关系管...     

Visualization of Isosurfaces with Parametric Cubes

To render images from volume datasets, an interpolation method also called reconstruction is needed. The level of details of the resultant image closely depends on the filter used for reconstruction. We propose here a new filter producing C ¹ continue surfaces. The provided image quality is better than current high-quality algorithms, like splatting or trilinear raycasting, where tiny details are often eliminated. In contrast with other studied high quality filters that are practically unusable, our algorithm has been implemented interactively on a modest platform thanks to an efficient implementation using parametric cubes. We also demonstrate the interest of a min-max octree in the visualization of isosurfaces interactively thresholded.     

Progressive light volume for interactive volumetric illumination

We propose a technique named progressive light volume to support advanced volumetric illumination effects, such as single scattering and multi scattering. The light volume stores direct lighting information for sample points of the volume data. Using the light volume, we are able to compute the direct lighting for any point in the volume data with a single texture lookup. In order to keep the rendering at an interactive frame rate, we build the light volume progressively if necessary. During the light volume construction period, we use a fast ray casting algorithm to produce a rough rendering estimate from the light volume. After the light volume is built, we use a path tracer to continuously estimate the light intensity for each pixel. Our method puts no restrictions on the number, position, and type of lights. We conducted a comprehensive evaluation for various datasets. The rendering results show that our method is able to produce compelling images, and the performance results indicate that our method is practical for interactive use. Copyright © 2016 John Wiley & Sons, Ltd.