{"title":"Volume visualization—a sleeping giant about to awaken","authors":"J. Foley","doi":"10.1109/VV.1998.10000","DOIUrl":"https://doi.org/10.1109/VV.1998.10000","url":null,"abstract":"","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"314 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1998-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125296804","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fast isocontouring for improved interactivity","authors":"C. Bajaj, Valerio Pascucci, D. Schikore","doi":"10.1109/SVV.1996.558041","DOIUrl":"https://doi.org/10.1109/SVV.1996.558041","url":null,"abstract":"We present an isocontouring algorithm which is near-optimal for real-time interaction and modification of isovalues in large datasets. A preprocessing step selects a subset S of the cells which are considered as seed cells. Given a particular isovalue, all cells in S which intersect the given isocontour are extracted using a high-performance range search. Each connected component is swept out using a fast isocontour propagation algorithm. The computational complexity for the repeated action of seed point selection and isocontour propagation is O(log n'+k), where n' is the size of S and k is the size of the output. In the worst case, n'=O(n), where n is the number of cells, while in practical cases, n' is smaller than n by one to two orders of magnitude. The general case of seed set construction for a convex complex of cells is described, in addition to a specialized algorithm suitable for meshes of regular topology, including rectilinear and curvilinear meshes.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1996-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122723247","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Multiscale 3D edge representation of volume data by a DOG wavelet","authors":"S. Muraki","doi":"10.1145/197938.197959","DOIUrl":"https://doi.org/10.1145/197938.197959","url":null,"abstract":"This paper proposes a method to expand volume data into the 3D DOG (D#wence of Gaz~~s&ns) functions by using the frame theory of non-orthogonal wavclcts. The spherically symmetric fcaturc of the 3D DOG fnnction is suitable for the visualization methods based on the volume density projection. Since the DOG function approximates a V”G (Laplacian of Gaussian) fnnction, the rcprcscntation can bc consiclcrcd as a hierarchy of the 3D cclgcs on diffcrcnt scales. Thcrcforc WC can cnhancc the cdgc information at will by blending the projection images on cliffcrcnt scales. Since the wavclct cocfficicnts have significant value whcrc the volume dcnsity changes, WC may nsc this rcprcscntation method for the cnhanccmcnt of the biomedical fcaturcs and also can WC it as a data compression method by ncglccting the insignificant coctficicnts. WC will apply onr rcprcscntation method to medical CT volume data and show the cfficicncy in &scribing the spatial structnrc of the volume.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130569448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Lossless compression of volume data","authors":"J. Fowler, R. Yagel","doi":"10.1145/197938.197961","DOIUrl":"https://doi.org/10.1145/197938.197961","url":null,"abstract":"Data in volume form consumes an extraordinary amount of storage space. For efficient storage and transmission of such data, compression algorithms are imperative. However, most volumetric datasets are used in biomedicine and other scientific applications where lossy compression is unacceptable. We present a lossless data-compression algorithm which, being oriented specifically for volume data, achieves greater compression performance than generic compression algorithms that are typically available on modern computer systems. Our algorithm is a combination of differential pulse-code modulation (DPCM) and Huffman coding and results in compression of around 50% for a set of volume data files.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127153420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A compact volume rendering accelerator","authors":"G. Knittel, W. Straßer","doi":"10.1145/197938.197968","DOIUrl":"https://doi.org/10.1145/197938.197968","url":null,"abstract":"We describe the architecture of a hardware accelerator for volume rendering. The system basically consists of four VLSI chips and the volume memory and represents a singleboard solution to the computational challenges of volume visualization. It generates arbitrary perspective projections, so that walk-through examinations are possible. The classification of structures of interest is an integral part of the rendering pipeline. Image quality is enhanced by providing Phong shading, depth-cueing and support for translucency. Despite its compactness and algorithmic complexity, the system is able to render 2563 data sets at a sustained frame generation rate of about 2.5Hz. CR","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127629840","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fast stereoscopic images with ray-traced volume rendering","authors":"S. Adelson, C. Hansen","doi":"10.1145/197938.197945","DOIUrl":"https://doi.org/10.1145/197938.197945","url":null,"abstract":"One of the drawbacks of standard volume rendering techniques is that is it often difficult to comprehend the three-dimensional structure of the volume from a single frame; this is especially true in cases where there is no solid surface. Generally, several frames must be generated and viewed sequentially, using motion parallax to relay depth. Another option is to generate a single spectroscopic pair, resulting in clear and unambiguous depth information in both static and moving images. Methods have been developed which take advantage of the coherence between the two halves of a stereo pair for polygon rendering and ray-tracing, generating the second half of the pair in significantly less time than that required to completely render a single image. This paper reports the results of implementing these techniques with parallel ray-traced volume rendering. In tests with different data types, the time savings is in the range of 70--80%.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"133 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126710916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Sorting and hardware assisted rendering for volume visualization","authors":"Clifford M. Stein, Barry G. Becker, N. Max","doi":"10.1145/197938.197971","DOIUrl":"https://doi.org/10.1145/197938.197971","url":null,"abstract":"We present some techniques for volume rendering unstructured data. Interpolation between vertex colors and opacities is performed using hardware assisted texture mapping, and color is integrated for use with a volume rendering system. We also present an O(n{sup 2}) method for sorting n arbitrarily shaped convex polyhedra prior to visualization. It generalizes the Newell, Newell and Sancha sort for polygons to 3-D volume elements.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126465001","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Volumetric ray tracing","authors":"L. Sobierajski, A. Kaufman","doi":"10.1145/197938.197949","DOIUrl":"https://doi.org/10.1145/197938.197949","url":null,"abstract":"This paper presents an eficient ray tracing method for scenes containing volumetric as well as geometric data. A global illumination equation is developed for this method, which is able to capture in a single image both realistic eaects and practical volume rendering. In this method, ray-object intersection calculations result in standard intersection points, as well as intersection segments. For accuracy and eflciency, all objects along a ray are sorted according to distance and intersection classification before any intersection calculations are pelformed. The intersection results are then passed to a shaden which evaluates the intensity equation defined by the illumination model to determine the final pixel value.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"59 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116521360","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Real-time previewing for volume visualization","authors":"Takafumi Saito","doi":"10.1145/197938.197974","DOIUrl":"https://doi.org/10.1145/197938.197974","url":null,"abstract":"A new method for volume visualization is proposed with the aim of real-time previewing of 3D scalar fields. Instead of voxels, hierarchically sampled points are used to store scalar values, where each sampled point has a priority value, and the set of points that have higher priority than any particular level are evenly distributed in 3D. In rendering, points are selected by priority level, scalar value, and gradient magnitude. Each selected point is drawn as a simple primitive such as a line(s) or polygon. With this approach, the high performance graphics hardware built into commercial workstations can directly accelerate drawing operations. This enables users to control viewing angle, clipping plane, and scalar values for isosurface in real-time or near real-time. The level of detail can be controlled for each frame to ensure constant time rendering. Also, by enhancing such geometric features as horiaontal and vertical lines on isosurface, viewers can understand the overview 3D shapes with a limited number of primitives.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115765751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Iso-contour volume rendering","authors":"J. Arvo, K. Novins","doi":"10.1145/197938.197977","DOIUrl":"https://doi.org/10.1145/197938.197977","url":null,"abstract":"In this paperwe presenta new approach to volume rendering in which curves of constant intensity in image space,or iso-contours, are computed directly for eachview. The generated iso-contours can be used to drive various visualization and feature-detection algorithms. The approach imposes no restriction on the organization of the data points and can accommodatea large class of radially-symmetric filter functions. The technique works well for both perspective and orthographic viewing projections. Each iso-contour is definedby an ordinary differential equation, which is solved numerically using a predictor-corrector method. A key element of the algorithm is the use of image intensity gradients, which we computeby means of a closedform expression that holds at every point on the image plane. A caching algorithm is described that dramatically accelerates the gradient computations on large datasets. The algorithm is demonstrated on emission-only datasets. We conclude by describing a number of possible enhancements.","PeriodicalId":124559,"journal":{"name":"Symposium on Volume Visualization","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1994-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127183941","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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