Although direct volume rendering is a powerful tool for visualizing complex structures within volume data, the size and complexity of the parameter space controlling the rendering process makes generating an informative rendering challenging. In particular, the specification of the transfer function --- the mapping from data values to renderable optical properties --- is frequently a time-consuming and unintuitive task. Ideally, the data being visualized should itself suggest an appropriate transfer function that brings out the features of interest without obscuring them with elements of little importance. We demonstrate that this is possible for a large class of scalar volume data, namely that where the regions of interest are the boundaries between different materials. A transfer function which makes boundaries readily visible can be generated from the relationship between three quantities: the data value and its first and second directional derivatives along the gradient direction. ...

We introduce a novel texture-based volume rendering approach that achieves the image quality of the best post-shading approaches with far less slices. It is suitable for new flexible consumer graphics hardware and provides high image quality even for low-resolution volume data and non-linear transfer functions with high frequencies, without the performance overhead caused by rendering additional interpolated slices. This is especially useful for volumetric effects in computer games and professional scientific volume visualization, which heavily depend on memory bandwidth and rasterization power.

Accurately and automatically conveying the structure of a volume model is a problem not fully solved by existing volume rendering approaches. Physics-based volume rendering approaches create images which may match the appearance of translucent materials in nature, but may not embody important structural details. Transfer function approaches allow flexible design of the volume appearance, but generally require substantial hand tuning for each new data set in order to be effective. We introduce the volume illustration approach, combining the familiarity of a physics-based illumination model with the ability to enhance important features using non-photorealistic rendering techniques. Since features to be enhanced are defined on the basis of local volume characteristics rather than volume sample value, the application of volume illustration techniques requires less manual tuning than the design of a good transfer function. Volume illustration provides a flexible unified framework for enhancing structural perception of volume models through the amplification of features and the addition of illumination effects.

Abstract—In this paper, we present a framework for high quality splatting based on elliptical Gaussian kernels. To avoid aliasing artifacts, we introduce the concept of a resampling filter, combining a reconstruction kernel with a low-pass filter. Because of the similarity to Heckbert’s EWA (elliptical weighted average) filter for texture mapping, we call our technique EWA splatting. Our framework allows us to derive EWA splat primitives for volume data and for point-sampled surface data. It provides high image quality without aliasing artifacts or excessive blurring for volume data and, additionally, features anisotropic texture filtering for point-sampled surfaces. It also handles nonspherical volume kernels efficiently; hence, it is suitable for regular, rectilinear, and irregular volume datasets. Moreover, our framework introduces a novel approach to compute the footprint function, facilitating efficient perspective projection of arbitrary elliptical kernels at very little additional cost. Finally, we show that EWA volume reconstruction kernels can be reduced to surface reconstruction kernels. This makes our splat primitive universal in rendering surface and volume data. Index Terms—Rendering systems, volume rendering, texture mapping, splatting, antialiasing. 1

We present Cube-4, a special-purpose volume rendering architecture that is capable of rendering high-resolution (e.g., 1024³) datasets at 30 frames per second. The underlying algorithm, called slice-parallel ray-casting, uses tri-linear interpolation of samples between data slices for parallel and perspective projections. The architecture uses a distributed interleaved memory, several parallel processing pipelines, and an innovative parallel dataflow scheme that requires no global communication, except at the pixel level. This leads to local, fixed bandwidth interconnections and has the benefits of high memory bandwidth, real-time data input, modularity, and scalability. We have simulated the architecture and have implemented a working prototype of the complete hardware on a configurable custom hardware machine. Our results indicate true real-time performance for high-resolution datasets and linear scalability of performance with the number of processing pipelines.

We present two beneficial rendering extensions to the Projected Tetrahedra (PT) algorithm by Shirley and Tuchman. These extensions are compatible with any cell sorting technique, for example the BSP-XMPVO sorting algorithm for unstructured meshes.

This paper presents a novel approach to assist the user in exploring appropriate transfer functions for the visualization of volumetric datasets. The search for a transfer function is treated as a parameter optimization problem and addressed with stochastic search techniques. Starting from an initial population of (random or pre-defined) transfer functions, the evolution of the stochastic algorithms is controlled by either direct user selection of intermediate images or automatic fitness evaluation using user-specified objective functions. This approach essentially shields the user from the complex and tedious "trial and error" approach, and demonstrates effective and convenient generation of transfer functions.

For volume rendering of regular grids the display of view-plane aligned slices has proven to yield both good quality and performance. In this paper we demonstrate how to merge the most important extensions of the original 3D slicing approach, namely the pre-integration technique, volumetric clipping, and advanced lighting. Our approach allows the suppression of clipping artifacts and achieves high quality while offering the flexibility to explore volume data sets interactively with arbitrary clip objects. We also outline how to utilize the proposed volumetric clipping approach for the display of segmented data sets. Moreover, we increase the rendering quality by implementing efficient over-sampling with the pixel shader of consumer graphics accelerators. We give prove that at least 4times over-sampling is needed to reconstruct the ray integral with sufficient accuracy even with pre-integration.

This paper describes a volume rendering system for unstructured data, especially finite element data, that creates images with very high accuracy. The system will currently handle meshes whose cells are either linear or quadratic tetrahedra. Compromises or approximations are not introduced for the sake of efficiency. Whenever possible, exact mathematical solutions for the radiance integrals involved and for interpolation are used. The system will also handle meshes with mixed cell types: tetrahedra, bricks, prisms, wedges, and pyramids, but not with high accuracy. Accurate semitransparent shaded isosurfaces may be embedded in the volume rendering. For very small cells, subpixel accumulation by splatting is used to avoid sampling error. A revision to an existing accurate visibility ordering algorithm is described which includes a correction and a method for dramatically increasing its efficiency. Finally, hardware assisted projection and compositing are extended from tetrahedra to arbit...

In this work we present a flexible framework for GPU-based volume rendering. The framework is based on a single pass volume raycasting approach and is easily extensible in terms of new shader functionality. We demonstrate the flexibility of our system by means of a number of high-quality standard and non-standard volume rendering techniques. Our implementation shows a promising performance in a number of benchmarks while producing images of higher accuracy than obtained by standard pre-integrated slice-based volume rendering.