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Building a highly accurate model for photovoltaic (PV) cells based on actual sampled data is essential for the simulation, optimization, evaluation, and control of photovoltaic power generation systems. But finding globally optimal model parameters, which give the best fit to experimental data, is a great challenge. In this paper, a new optimization algorithm, called the micro-charge field effect P systems optimization algorithm (MFE-POA) is proposed. Though the analysis of the interaction among ionic substances inside a living cell membrane and considering the algorithm’s dual needs of exploration and convergence accuracy, combined with the law of interaction between charges, we designed a novel micro-charge interaction rule based on distance, force characteristics, spatial location, and percentage of search completion, and embedded it into our existing P systems optimization algorithm (POA). Numerical studies and results analysis on some benchmark test functions demonstrate that MFE-POA can produce solutions of high quality and has great stability. The proposed method is applied to the model parameter estimation of the two types of PV cell models and multi-cell PV modules in different environmental conditions. The experimental results clearly argue the effectiveness of our proposed MFE-POA. Comparisons with other methods are presented and the results show that the proposed optimization algorithm is helpful and worth great promoting for parameter estimation in renewable energy modeling and prediction.

The ocean surface is highly dynamic. It moves rapidly and thus its shading changes rapidly as well. Usually, this doesn't pose any problems if the shading is smooth. However, for a surface that has a strong highlight or bright reflection moving rapidly, it causes an inaccurate and unnatural flickering. In the traditional rendering algorithms, each frame is rendered independently at a discrete time, resulting in serious temporal aliasing artifacts. Particularly, for a wavy water surface, reflection vectors may not hit the light source even though they actually hit for part of the frame time. Removing such aliasing in real-time is an active research area and many methods have been proposed [Jimenez et al. 2011]. They can improve the fidelity and efficiency of the rendering method. However, their focus is on spatial anti-aliasing and most of them do not address the temporal aliasing problem, particularly the one observed in rendering a reflected image of a light source on the water surface.

© 2017, Springer-Verlag Berlin Heidelberg. Scenes in computer animation can have extreme complexity, especially when high resolution objects are placed in the distance and occupy only a few pixels. A useful technique for level of detail in these cases is to use a sparse voxel octree containing both hard surfaces and a participating medium consisting of microflakes. In this paper, we discuss three different methods for approximating the distribution of normals of the microflakes, which is needed to compute extinction, inscattering of attenuated direct illumination, and multiple scattering in the participating medium. Specifically, we consider (a) k means approximation with k weighted representatives, (b) expansion in spherical harmonics, and (c) the distribution of the normals of a specific ellipsoid. We compare their image quality, data size, and computation time.

Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.

Most 3D vector field visualization techniques suffer from the problem of visual clutter, and it remains a challenging task to effectively convey both directional and structural information of 3D vector fields. In this paper, we present a novel visualization framework that combines the advantages of clustering methods and illustrative rendering techniques to generate a concise and informative depiction of complex flow structures. Given a 3D vector field, we first generate a number of streamlines covering the important regions based on an entropy measurement. Then we decompose the streamlines into different groups based on a categorization of vector information, wherein the streamline pattern in each group is ensured to be coherent or nearly coherent. For each group, we select a set of representative streamlines and render them in an illustrative fashion to enhance depth cues and succinctly show local flow characteristics. The results demonstrate that our approach can generate a visualization that is relatively free of visual clutter while facilitating perception of salient information of complex vector fields.

Isosurfaces are fundamental volumetric visualization tools and are generated by approximating contours of trilinearly interpolated scalar fields. While a complete set of cases has recently been published by Nielson, the formal proof that these cases are the only ones possible and that they are topologically correct is difficult to follow. We present a more straightforward proof of the correctness and completeness of these cases based on a variation of the Dividing Cubes algorithm. Since this proof is based on topological arguments and a divide-and-conquer approach, this also sets the stage for developing tessellation cases for higher order interpolants and the quadrilinear interpolant in four dimensions. We also demonstrate that apart from degenerate cases, Nielson's cases are, in fact, subsets of two basic configurations of the trilinear interpolant.

We have simulated a time varying wind field using the lattice Boltzmann model, and its effect on blades of grass with a simple mass-spring model. We present a global illumination model for multiple scattering of incident sun and sky illumination within the field of grass. We model the grass as a continuous distribution of infinitesimal colored scattering flakes and solve a system of differential equations for the radiance transport. We repeat this for a collection of grass bending directions and amounts, and then interpolate the solutions when rendering animations of blowing grass.

This paper presents a method to accelerate algorithms that need a correct and complete visibility ordering of their data for rendering. The technique works by pre-sorting primitives in object-space using three lists (one for each axis: X, Y and Z), and then combining the lists using graphics hardware by rendering each list to a texture and merging the textures in the end. We validate our algorithm by applying it to the splatting technique using several types of rendering, including point-based rendering and volume rendering. We also detail our hardware implementation for volume rendering using point sprites.

It is known that the pure light field approach for view synthesis relies on a large number of image samples to produce anti-aliased renderings. Otherwise, the insufficiency of image sampling needs to be compensated for by geometry sampling. Currently, geometry estimation is done either offline or using dedicated hardware. Our solution to this dilemma is based on three key ideas: a formal analysis of the equivalency between light field rendering and plane-based warping, multi focus imaging in a multi camera system by plane sweeping, and the fusion of the multi focus image using multi view stereo. The essence of our method is to perform necessary depth estimation up to the level required by the minimal joint image-geometry sampling rate using off-the-shelf graphics hardware. As a result, real-time anti-aliased light field rendering is achieved even if the image samples are insufficient.

The SciDAC Institute for Ultrascale Visualization brought together leading experts from visualization, high-performance computing, and science application areas to make advanced visualization solutions for SciDAC scientists and the broader community. Over the five-year project, the Institute introduced many new enabling visualization techniques, which have significantly enhanced scientists’ ability to validate their simulations, interpret their data, and communicate with others about their work and findings. This Institute project involved a large number of junior and student researchers, who received the opportunities to work on some of the most challenging science applications and gain access to the most powerful high-performance computing facilities in the world. They were readily trained and prepared for facing the greater challenges presented by extreme-scale computing. The Institute’s outreach efforts, through publications, workshops and tutorials, successfully disseminated the new knowledge and technologies to the SciDAC and the broader scientific communities. The scientific findings and experience of the Institute team helped plan the SciDAC3 program.

Images synthesized by light field rendering exhibit aliasing artifacts when the light field is undersampled; adding new light field samples improves the image quality and reduces aliasing but new samples are expensive to acquire. Light field rays are traditionally gathered directly from the source images, but new rays can also be inferred through geometry estimation. This paper describes a light field rendering approach based on this principle that estimates geometry from the set of source images using multi-baseline stereo reconstruction to supplement the existing light field rays to meet the minimum sampling requirement. The rendering and reconstruction steps are computed over a set of planes in the scene volume, and output images are synthesized by compositing results from these planes together. The planes are each processed independently and the number of planes can be adjusted to scale the amount of computation to achieve the desired frame rate. The reconstruction fidelity (and by extension image quality) is improved by a library of matching templates to support matches along discontinuities in the image or geometry (e.g. object profiles and concavities). Given a set of silhouette images, the visual hull can be constructed and applied to further improve reconstruction by removing outlier matches. The algorithm is efficiently implemented by a set of image filter operations on commodity graphics hardware and achieves image synthesis at interactive rates.

Visualization of observed data or simulation output is important to science and engineering. I have been particularly interested in visualizing 3-D structures, and report here my personal impressions on progress in the last 20 years in visualizing molecules, scalar fields, and vector fields and their associated flows. I have tried to keep the survey and list of references manageable, so apologize to those authors whose techniques I have not mentioned, or have described without a reference citation.

Most existing light-field rendering methods rely on images that record the color of the rays. In this paper, we present a new approach that instead uses colored point clouds, which are the source of the rays. Furthermore, we study the light field from a dual-space viewpoint, where 3D scene points appear as geometry hyperlines, and rays appear as hyperpoints located on the hyperlines. Rendering the light field reduces to finding and blending the closest hyperlines to the hyperpoints corresponding to the virtual rays. Occlusion is dealt with by clustering nearby hyperlines according to their slope. Hole filling is dealt with by increasing the range of contribution of the hyperlines by a given threshold. We also propose the concept of local ray space, and show that it improves the rendering quality and removes the restriction on virtual camera position that is associated with the global ray space scheme. Finally, we show how to deal with uncertain geometric information in our framework.

Projection methods for volume rendering unstructured data work by projecting, in visibility order, the polyhedral cells of the mesh onto the image plane, and incrementally compositing each cell's color and opacity into the final image. Normally, such methods require an algorithm to determine a visibility order of the cells. The Meshed Polyhedra Visibility Order (MPVO) algorithm can provide such an order for convex meshes by considering the implications of local ordering relations between cells sharing a common face. However, in nonconvex meshes, one must also consider ordering relations along viewing rays which cross empty space between cells. In order to include these relations, the algorithm described in this paper, the scanning exact meshed polyhedra visibility ordering (SXMPVO) algorithm, scan-converts the exterior faces of the mesh and saves the ray-face intersections in an A-Buffer data structure which is then used for retrieving the extra ordering relations. The image which SXMPVO produces is the same as would be produced by ordering the cells exactly, even though SXMPVO does not compute an exact visibility ordering. This is because the image resolution used for computing the visibility ordering relations is the same as that which is used for the actual volume rendering and we choose our A-Buffer rays at the same sample points that are used to establish a polygon's pixel coverage during hardware scan conversion. Thus, the algorithm is image-space correct. The SXMPVO algorithm has several desirable features; among them are speed, simplicity of implementation, and no extra (i.e., with respect to MPVO) preprocessing.

One step in the reconstruction pipeline for creating scene geometry from multiple camera views is the fitting of 3-D planes to image segments. We optimize the four homogeneous coefficients of the equation of a plane, so that the homography it induces on a source image segment minimizes a cost function with photo consistency and edge consistency terms. The photo consistency term for a segment is defined as the summed squared pixel color differences with all target images in which it is visible. For the edges we find a set of sub pixel-precise Canny edge points from the source image. The edge consistency term considers all pairs of segments which are adjacent in 3D, and sums the squared 2D distances of the appropriate Canny edge points to the projection of the line in which the two segment planes intersect. We apply the L-BFGS non-linear optimization algorithm, which uses derivatives of the cost function with respect to the plane equation coefficients, and we derive analytic formulas for these derivatives for both terms in the cost function. An alternate optimization method uses the sparse Hessian matrix of second derivatives, and we compute these second derivatives as well. We test these plane optimizations on both synthetic and real image sequences.

Uncertainty arises in all stages of the visualization pipeline. However, the majority of flow visualization applications convey no uncertainty information to the user. In tools where uncertainty is conveyed, the focus is generally on data, such as error that stems from numerical methods used to generate a simulation or on uncertainty associated with mapping visualiza-tion primitives to data. Our work is aimed at another source of uncertainty - that associated with user-controlled input param-eters. The navigation and stability analysis of user-parameters has received increasing attention recently. This work presents an investigation of this topic for flow visualization, specifically for three-dimensional streamline and pathline seeding. From a dynamical systems point of view, seeding can be formulated as a predictability problem based on an initial condition. Small perturbations in the initial value may result in large changes in the streamline in regions of high unpredictability. Analyzing this predictability quantifies the perturbation a trajectory is subjugated to by the flow. In other words, some predictions are less certain than others as a function of initial conditions. We introduce novel techniques to visualize important user input parameters such as streamline and pathline seeding position in both space and time, seeding rake position and orientation, and inter-seed spacing. The implementation is based on a metric which quantifies similarity between stream and pathlines. This is important for Computational Fluid Dynamics (CFD) engineers as, even with the variety of seeding strategies available, manual seeding using a rake is ubiquitous. We present methods to quantify and visualize the effects that changes in user-controlled input parameters have on the resulting stream and pathlines. We also present various visualizations to help CFD scientists to intuitively and effectively navigate this parameter space. The reaction from a domain expert in fluid dynamics is also reported.

Automatic fusion of aerial optical imagery and untextured LiDAR data has been of significant interest for generating photo-realistic 3D urban models in recent years. However, unsupervised, robust registration still remains a challenge. This paper presents a new registration method that does not require priori knowledge such as GPS/INS information. The proposed algorithm is based on feature correspondence between a LiDAR depth map and a depth map from an optical image. Each optical depth map is generated from edge-preserving dense correspondence between the image and another optical image, followed by ground plane estimation and alignment for depth consistency. Our two-pass RANSAC with Maximum Likelihood estimation incorporates 2D-2D and 2D-3D correspondences to yield robust camera pose estimation. Experiments with a LiDAR-optical imagery dataset show promising results, without using initial pose information.

A hardware polygon rendering pipeline can be used with hardware compositing to volume render arbitrary unstructured grids composed of convex polyhedral cells. This technique is described, together with the global sorting necessary for back-to-front compos- iting, and the modifications that must be made to approximate cur- vilinear cells, whose faces may not be planar. © 2000 John Wiley & Sons

Author(s): Wang, Wencheng; Wu, En-Hua; Max, Nelson | Abstract: Selective visualization is a solution for visualizing data of large size and dimensionality. In this paper a new method is proposed for effectively rendering certain chosen parts among the full set of data in terms of a colour buffer, referred to as the virtual plane, for storing intermediate results. By this method, scientists may concentrate their attention on the contents of data in which they are interested. Besides, the method could be easily integrated with all the current direct volume rendering techniques, especially progressive refinement methods and selective methods.

This paper presents a multi-view stereo algorithm for piecewise planar scene reconstruction and optimization. Our segmentation-based reconstruction algorithm is iterative to minimize our defined energy function, consisting of reconstruction, refinement and optimization steps. The first step is a plane initialization to allow each segment to have a set of initial plane candidates. Then a plane refinement based on non-linear optimization improves the accuracy of the segment planes. Finally a plane optimization with a segment-adjacency graph leads to optimal segment planes, each of which is chosen among possible plane candidates by evaluating its relationship with adjacent planes in 3D. This algorithm yields better accuracy and performance, compared to the previous algorithms described in this paper. The results show our method is suitable for outdoor or aerial urban scene reconstruction, especially in wide baselines and images with textureless regions.

BuildBeta is a feature of the ProteinShop software designed to thoroughly sample a protein conformational space given the protein's sequence of amino acids and secondary structure predictions. It targets proteins with beta sheets because they are particularly challenging to predict due to the complexity of sampling long-range strand pairings. Here we discuss some of the most difficult targets in the recent 9th Community Wide Experiment on the Critical Assessment of Techniques for Protein Structure Prediction (CASP9) and show how BuildBeta can leverage some of the most successful methods in the category "template-free modeling" by augmenting their sampling capabilities. We also discuss ongoing efforts to improve the quality of the supersecondary structures it generates.

We present two new techniques for rendering 3D vector fields in scientific visualisation. We also present a new technique called texture splats for rendering these volumes efficiently. >

Techniques for visualizing several climate variables, particularly clouds and wind velocities, are discussed. The techniques are volume rendering, textured contour surfaces, and vector field rendering. The application of these techniques is discussed in the context of a high-definition television (HDTV) animation produced to show global cloud motion during ten simulated days in January. The computational grid is defined by nearly a million grid points-320 evenly spaced longitudes, 160 unevenly spaced latitudes, and 19 unevenly spaced surfaces of constant geopotential. The climate variables at every grid point were output at every hour of simulated time, resulting in 380 MB of data per simulated day. >

We propose a new fast height-field rendering method for Image-Based Lighting. Our approach approximates the environmental illumination using spherical radial basis functions (SRBFs). We approximate the integrand of the rendering equation as a sum of products of the SRBFs and the visibility function. Then we solve the integral by approximating the visibility function of each SRBF as the fraction visible above the height-field. This fraction is precomputed into a 2-Dtexture, as a function of the SRBF size and its angle to the horizon. We use two different approximations of the horizon. The first, called a horizon map, can render more accurate self occlusion. The second, called a cone map, needs only a single RGBA 2D texture but can only render rough self-shadowing. Our approach can quickly render shading and self-shadowing of a height-field from all-frequency environmental lighting.

Assume that the sun, sky, and clouds are represented as a raster image on a plane at infinity, and the shadows of a tree canopy are represented as a raster transparency mask on a canopy plane. Then the illumination on the ground is the correlation of these two rasters, which can be rapidly computed by fast Fourier transform techniques.

International audience; We propose an algorithm for the real time realistic simulation of multiple anisotropic scattering of light in a volume. Contrary to previous real-time methods we account for all kinds of light paths through the medium and preserve their anisotropic behavior. Our approach consists of estimating the energy transport from the illuminated cloud surface to the rendered cloud pixel for each separate order of multiple scattering. We represent the distribution of light paths reaching a given viewed cloud pixel with the mean and standard deviation of their entry points on the lit surface, which we call the collector area. At rendering time for each pixel we determine the collector area on the lit cloud surface for different sets of scattering orders, then we infer the associated light transport. The fast computation of the collector area and light transport is possible thanks to a preliminary analysis of multiple scattering in planeparallel slabs and does not require slicing or marching through the volume. Rendering is done efficiently in a shader on the GPU, relying on a cloud surface mesh augmented with a Hypertexture to enrich the shape and silhouette. We demonstrate our model with the interactive rendering of detailed animated cumulus and cloudy sky at 2-10 frames per second.

This paper discusses a three-pass raster motion-blur algorithm (and some generalizations) in the context of texture-mapped polygons and its application to blurring objects and surfaces made up of multiple polygons, which may move in different directions.

The output of a scan-line visible-surface algorithm is a collection of scan-line segments with associated simple shading functions, which together define the shading as a function of a continuous variable along each scan line. A hybrid antialiasing method that uses this information fully is presented. The method extends to the case where an image transform maps the scan lines into slanted lines in the output raster coordinates. Edge-slope information can be used to infer data along extra scan lines to improve antialiasing. Results obtained with the method are given. >

We present the application of hardware accelerated volume rendering algorithms to the simulation of radiographs as an aid to scientists designing experiments, validating simulation codes, and understanding experimental data. The techniques presented take advantage of 32-bit floating point texture capabilities to obtain solutions to the radiative transport equation for X-rays. The hardware accelerated solutions are accurate enough to enable scientists to explore the experimental design space with greater efficiency than the methods currently in use. An unsorted hexahedron projection algorithm is presented for curvilinear hexahedral meshes that produces simulated radiographs in the absorption-only regime. A sorted tetrahedral projection algorithm is presented that simulates radiographs of emissive materials. We apply the tetrahedral projection algorithm to the simulation of experimental diagnostics for inertial confinement fusion experiments on a laser at the University of Rochester.

VisIt is a richly featured visualization tool that is used to visualize some of the largest simulations ever run. The scale of these simulations requires that optimizations are incorporated into every operation VisIt performs. But the set of applicable optimizations that VisIt can perform is dependent on the types of operations being done. Complicating the issue, VisIt has a plugin capability that allows new, unforeseen components to be added, making it even harder to determine which optimizations can be applied. We introduce the concept of a contract to the standard data flow network design. This contract enables each component of the data flow network to modify the set of optimizations used. In addition, the contract allows for new components to be accommodated gracefully within VisIt's data flow network system.

Much of the previous work in the large data visualization area has solely focused on handling the scale of the data. This task is clearly a great challenge and necessary, but it is not sufficient. Applying standard visualization techniques to large scale data sets often creates complicated pictures where meaningful trends are lost. A second challenge, then, is to also provide algorithms that simplify what an analyst must understand, using either visual or quantitative means. This challenge can be summarized as improving the legibility or reducing the complexity of massive data sets. Fully meeting both of these challenges is the work of many, many PhD dissertations. In this dissertation, we describe some new techniques to address both the scale and legibility challenges, in hope of contributing to the larger solution. In addition to our assumption of simultaneously addressing both scale and legibility, we add an additional requirement that the solutions considered fit well within an interoperable framework for diverse algorithms, because a large suite of algorithms is often necessary to fully understand complex data sets. For scale, we present a general architecture for handling large data, as well as details of a contract-based system for integrating advanced optimizations into a data flow network design. We also describe techniques for volume rendering and performing comparisons at the extreme scale. For legibility, we present several techniques. Most noteworthy are equivalence class functions, a technique to drive visualizations using statistical methods, and line-scan based techniques for characterizing shape.

The bump-mapping technique is often used to represent bumps on objects such as bark on trees and craters on the moon. In order to render shadows cast by bumps, the horizon map method was proposed. The horizon map is a table which has, for each of a small collection of azimuthal directions, slopes from each viewpoint on the bump map (height field) to the corresponding horizon point, which is the highest viewable point seen from that viewpoint. We propose a more precise method for rendering bumpmap shadows using a both a horizon map and a distance map, to take curvature of surfaces into consideration. The distance map is a table, which has, for each azimuthal direction, horizontal projected distances from each point of the bump map to its corresponding horizon point. The proposed method can render shadows efficiently by using programmable graphics hardware.

One of the grand challenges in computational biology is the prediction of the three-dimensional structure of a protein, which determines its function, from its chemical makeup alone. A protein's primary structure, i. e., its amino acid sequence, is directly encoded in its DNA sequence,which is a purely one-dimensional structure that does not directly encode a three-dimensional shape. It is commonly believed that the native shape of a protein is the one corresponding to the global minimum of its internal energy; thus, the protein folding problem has been treated as an optimization problem in recent years. It is important to start solving any optimization problem from a good set of initial configurations that allow the optimization code to, ideally, search the complete optimization space for a global minimum. Our work focuses on providing an interactive, visual tool to rapidly create many initial configurations for a given amino acid sequence, which are then used as input for an optimization algorithm.

We review the cell projection method of volume rendering, discussing back-to-front cell sorting, and approximations involved in hardware color computation and interpolation. We describe how the method accommodates cells with non-planar faces using view dependent subdivision into tetrahedra.

Computer animation of outdoor scenes is enhanced by realistic clouds. I discuss several different modelling and rendering schemes for clouds, and show how they evolved in my animation work. These include transparency-textured clouds on a 2D plane, smooth shaded or textured 3D cloud surfaces, and 3D volume rendering. For the volume rendering, I present various illumination schemes, including the density emitter, single scattering, and multiple scattering models. >

We propose to look at light fields from a dual space point of view. The advantage, in addition to revealing some new insights, is a framework that combines the benefits of many existing works. Using the well known two-plane-parameterization, we derive the duality between the 4-D light field and the 3-D world space. In the dual light field, rays become hyper points. We introduce the concept of hyperline. Then, cameras appear as hyperlines - camera hyperline (CHL) - mostly heterogeneous in color; scene points also appear as hyperlines - geometry hyperline (GHL) - mostly homogeneous in color. CHL's and GHL's are independent. The existence of one does not require or replace the other. When both exist, they cross each other at the dual ray hyper points. Both CHL and GHL-based light field rendering results are presented.

In this paper we present a system for visualizing volume data from remote supercomputers. We have developed both parallel volume rendering algorithms, and the World Wide Web (WWW) software for accessing the data at the remote sites. The implementation uses Hypertext Markup Language, Java, and Common Gateway Interface scripts to connect WWW servers/clients to our volume renderers. The front ends are interactive Java classes for specification of view, shading , and classification inputs. We present performance results, and implementation details for connections to our computing resources at the University of California Santa Cruz including a MasPar MP-2, SGI Reality Engine-RE2, and SGI Challenge machines. We apply the system to the task of visualizing trabecular bone from finite element simulations. Fast volume rendering on remote compute servers through a web interface allows us to increase the accessibility of the results to more users. User interface issues, overview of parallel algorithm developments, and overall system interfaces and protocols are presented. Access is available through Uniform Resource Locator http://www.cse.ucsc.edu/research/slvg/.

Chen and Williams [2] show how precomputed z-buffer images from different fixed viewing positions can be reprojected to produce an image for a new viewpoint. Here, images are precomputed for twigs and branches at various levels in the hierarchical structure of a tree, and adaptively combined depending on the position of the new viewpoint. The precomputed images contain multiple z levels to avoid missing pixels in the reconstruction, subpixel masks for antialiasing, and colors and normals for shading after reprojection.

Realistic rendering of participating media like clouds requires multiple anisotropic light scattering. This paper presents a propagation approximation for light scattered into M direction bins, which reduces the “ray effect” problem in the traditional “discrete ordinates” method. For a regular grid volume of n 3 elements, it takes O(Mn 3 log n + M 2 n 3) time and 0(Mn 3 + M 2) space.

Parallel projection z-buffer images are precomputed for a number of preset viewing directions on the unit sphere. Using the depth information, we can reconstruct a 3-D point from each image pixel. Then parallel or perspective views can be found from any other viewpoint by rotating the 3-D points from the nearest three or four precomputed views into the proper position and projecting them onto an output z-buffer. A temporary z-buffer image, constructed in the same way for a viewpoint at the light source, is used for a z-buffer shadow algorithm. The rendering algorithm is applied to broad leaf and needle leaf trees, and tested in animation. Our rendering algorithm is similar to that in Chen and Williams [1], with differences listed below.

A method is described for switching smoothly between rendering algorithms as required by the amount of visible surface detail. The result will be more realism with less computation for displaying objects whose surface detail can be described by one or more bump maps. The three rendering algorithms considered are a BRDF, bump mapping, and displacement mapping. The bump mapping has been modified to make it consistent with the other two. For a given viewpoint, one of these algorithms will show a better trade-off between quality, computation time, and aliasing than the other two. The decision as to which algorithm is appropriate is a function of distance, viewing angle, and the frequency of bumps in the bump map.

Simulation of complex 3D phenomena generate data sets which are hard to comprehend using conventional 2D oriented visualization tools. One way to overcome this limitation is to use various volume visualization techniques. While early volume visualization techniques worked well on simple scalar volumes they failed to exploit frame buffer hardware capabilities and handle higher order data such as vector fields. Work at Lawrence Livermore National Laboratory has centered on developing new techniques and extending existing techniques. This paper describes the various algorithms developed for volume rendering, and presents new methods of examining vector fields in a volumetric fashion.

Algorithms are presented for raster and vector motion blur, which produce images and masks suitable for combination by the 21/2-D compositing process. The raster algorithm is based on a "skew, blur, unskew" scheme, using a very efficient one-dimensional blurring algorithm. The vector algorithm extends the ideas of anti-aliased scan conversion to motion blur.

A method of simulating transparency for intersecting-sphere molecular models is described, which combines computer graphics and optical printing. A modification produces efficient shadow approximations, using a view from the light source to find the illuminated fraction of each sphere.

An area-based algorithm for space-filling molecular models, which computes the visible regions of each atom sphere at floating-point precision, has been used to produce hard-edged shadows. The algorithm is repeated from the point of view of the light source in the YZ plane, and the visible regions are then transformed into the illuminated regions in the final view. The cost of the visibility calculations is independent of the resolution of the raster.

The shadow volume algorithm of Frank Crow was reorganized to provide information on the regions of illuminated space in front of each visible surface. This information is used to calculate the extra intensity due to atmospheric scattering, so when the atmosphere is partly in shadow, columns of scattered light will be visible. For efficiency in sorting the shadow edges, the image is computed in polar coordinates.