Simulating hand-drawn illustration techniques can succinctly express information in a manner that is communicative and informative. We present a framework for an interactive direct volume illustration system that simulates traditional stipple drawing. By combining the principles of artistic and scientific illustration, we explore several feature enhancement techniques to create effective, interactive visualizations of scientific and medical datasets. We also introduce a rendering mechanism that generates appropriate point lists at all resolutions during an automatic preprocess, and modifies rendering styles through different combinations of these feature enhancements. The new system is an effective way to interactively preview large, complex volume datasets in a concise, meaningful, and illustrative manner. Volume stippling is effective for many applications and provides a quick and efficient method to investigate volume models.

AbstractÐIn this paper, we present a two-level approach for volume rendering, i.e., two-level volume rendering, which allows for selectively using different rendering techniques for different subsets of a 3D data set. Different structures within the data set are rendered locally on an object-by-object basis by either DVR, MIP, surface rendering, value integration (x-ray-like images), or nonphotorealistic rendering. All the results of subsequent object renderings are combined globally in a merging step (usually compositing in our case). This allows us to selectively choose the most suitable technique for depicting each object within the data while keeping the amount of information contained in the image at a reasonable level. This is especially useful when inner structures should be visualized together with semitransparent outer parts, similar to the focus-plus-context approach known from information visualization. We also present an implementation of our approach which allows us to explore volumetric data using two-level rendering at interactive frame rates. Index TermsÐVisualization, volume rendering, dynamical systems, medical applications. æ 1

In this paper we present a fast visualization technique for volumetric data, which is based on a recent nonphotorealistic rendering technique. Our new approach enables alternative insights into 3D data sets (compared to traditional approaches such as direct volume rendering or iso-surface rendering). Object contours, which usually are characterized by locally high gradient values, are visualized regardless of their density values. Cumbersome tuning of transfer functions, as usually needed for setting up DVR views is avoided. Instead, a small number of parameters is available to adjust the non-photorealistic display. Based on the magnitude of local gradient information as well as on the angle between viewing direction and gradient vector, data values are mapped to visual properties (color, opacity), which then are combined to form the rendered image (MIP is proposed as the default compositing stragtegy here). Due to the fast implementation of this alternative rendering approach, it is possible to interactively investigate the 3D data, and quickly learn about internal structures. Several further extensions of our new approach, such as level lines are also presented in this paper. Key words: interactive volume rendering, non-photorealistic rendering, shear-warp projection. 1.

In this paper we present a two-level approach for fusing direct volume rendering (DVR) and maximum-intensity projection (MIP) within a joint rendering method. Dierent structures within the data-set are rendered locally by either MIP or DVR on an object-by-object basis. Globally all the results of subsequent object renderings are combined in a merging step (usually compositing in our case). This allows to selectively choose the most suitable technique for depicting each object within the data, while keeping the amount of information contained in the image at a reasonable level. This is especially useful when inner structures should be visualized together with semi-transparent outer parts, similar to the focus-and-context approach known from information visualization. We also present an implementation of our approach, which allows to explore volumetric data using twolevel rendering at interactive frame rates.

Volume illustration is a developing trend in volume visualization, focused on conveying volume information effectively by enhancing interesting features of the volume and omitting insignificant data. However, the calculations involved have limited the illustration process to noninteractive rendering. We have developed a new interactive volume illustration system (IVIS) that harnesses the power of programmable graphics processors, and includes a novel approach for feature halo enhancement. This interactive illustration system is a powerful tool for exploration and analysis of volumetric datasets.

Most CPU-based volume raycasting approaches achieve high performance by advanced memory layouts, space subdivision, and excessive pre-computing. Such approaches typically need an enormous amount of memory. They are limited to sizes which do not satisfy the medical data used in daily clinical routine. We present a new volume raycasting approach based on image-ordered raycasting with object-ordered processing, which is able to perform highquality rendering of very large medical data in real-time on commodity computers. For large medical data such as computed tomographic (CT) angiography run-offs (512x512x1202) we achieve rendering times up to 2.5 fps on a commodity notebook. We achieve this by introducing a memory efficient acceleration technique for on-the-fly gradient estimation and a memory efficient hybrid removal and skipping technique of transparent regions. We employ quantized binary histograms, granular resolution octrees, and a cell invisibility cache. These acceleration structures require just a small extra storage of approximately 10%.

Ideal reconstruction filters, for function or arbitrary derivative reconstruction, have to be bounded in order to be practicable since they are infinite in their spatial extent. This can be accomplished by multiplying them with windowing functions. In this paper we discuss and assess the quality of commonly used windows and show that most of them are unsatisfactory in terms of numerical accuracy. The best performing windows are Blackman, Kaiser and Gaussian win- ftheussl,helwig,meisterg@cg.tuwien.ac.at dows. The latter two are particularly useful since both have a parameter to control their shape, which, on the other hand, requires to find appropriate values for these parameters. We show how to derive optimal parameter values for Kaiser and Gaussian windows using a Taylor series expansion of the convolution sum. Optimal values for function and first derivative reconstruction for window widths of two, three, four and five are presented explicitly. Keywords: ideal reconstruction, wind...

294,018 vertices, compressed to 0.7437 bits per face. C: UNC CThead data set, level 1160, 312,488 faces, 312,287 vertices, compressed to 0.8081 bits per face. In this paper we introduce a new and simple algorithm to compress isosurface data. This is the data extracted by isosurface algorithms from scalar functions defined on volume grids, and used to generate polygon meshes or alternative representations. In this algorithm the mesh connectivity and a substantial proportion of the geometric information are encoded to a fraction of a bit per Marching Cubes vertex with a context based arithmetic coder closely related to the JBIG binary image compression standard. The remaining optional geometric information that specifies the location of each Marching Cubes vertex more precisely along its supporting intersecting grid edge, is efficiently encoded in scan-order with the same mechanism. Vertex normals can optionally be computed as normalized gradient vectors by the encoder and included in the bitstream after quantization and entropy encoding, or computed by the decoder in a postprocessing smoothing step. These choices are determined by trade-offs associated with an in-core vs. out-of-core decoder structure. The main features of our algorithm are its extreme simplicity and high compression rates.

The size of volumetric datasets used in medical environments is increasing at a rapid pace. Due to excessive pre-computation and memory demanding data structures, most current approaches for volume visualization do not meet the requirements of daily clinical routine. In this diploma thesis, an approach for interactive high-quality rendering of large medical data is presented. It is based on image-order raycasting with object-order data traversal, using an optimized cache coherent memory layout. New techniques and parallelization strategies for direct volume rendering of large data on commodity hardware are presented. By using new memory efficient acceleration data structures, high-quality direct volume rendering of several hundred megabyte sized datasets at sub-second frame rates on a commodity notebook is achieved.

In this paper we present a compression technique for efficiently representing boundary objects from volumetric data-sets. Exploiting spatial coherency within object contours, we are able to reduce the size of the volumetric boundary down to the size of just a few images. Allowing for direct volume rendering of the down-scaled data in addition to compression ratios up to 250:1, interactive volume visualization becomes possible, even over the Internet and on a low-end PC.