Torsten Möller, K. Mueller, Y. Kurzion, R. Machiraju, R. Yagel
The correct choice of function and derivative reconstruction filters is paramount to obtaining highly accurate renderings. Most filter choices are limited to a set of commonly used functions, and the visualization practitioner has so far no way to state his preferences in a convenient fashion. Much work has been done towards the design and specification of filters using frequency based methods. However for visualization algorithms it is more natural to specify a filter in terms of the smoothness of the resulting reconstructed function and the spatial reconstruction error. Hence, the authors present a methodology for designing filters based on spatial smoothness and accuracy criteria. They first state their design criteria and then provide an example of a filter design exercise. They also use the filters so designed for volume rendering of sampled data sets and a synthetic test function. They demonstrate that their results compare favorably with existing methods.
{"title":"Design of accurate and smooth filters for function and derivative reconstruction","authors":"Torsten Möller, K. Mueller, Y. Kurzion, R. Machiraju, R. Yagel","doi":"10.1145/288126.288189","DOIUrl":"https://doi.org/10.1145/288126.288189","url":null,"abstract":"The correct choice of function and derivative reconstruction filters is paramount to obtaining highly accurate renderings. Most filter choices are limited to a set of commonly used functions, and the visualization practitioner has so far no way to state his preferences in a convenient fashion. Much work has been done towards the design and specification of filters using frequency based methods. However for visualization algorithms it is more natural to specify a filter in terms of the smoothness of the resulting reconstructed function and the spatial reconstruction error. Hence, the authors present a methodology for designing filters based on spatial smoothness and accuracy criteria. They first state their design criteria and then provide an example of a filter design exercise. They also use the filters so designed for volume rendering of sampled data sets and a synthetic test function. They demonstrate that their results compare favorably with existing methods.","PeriodicalId":167141,"journal":{"name":"IEEE Symposium on Volume Visualization (Cat. No.989EX300)","volume":"28 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":"134313379","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}
High quality rendering and physics based modeling in volume graphics have been limited because intensity based volumetric data do not represent surfaces well. High spatial frequencies due to abrupt intensity changes at object surfaces result in jagged or terraced surfaces in rendered images. The use of a distance-to-closest-surface function to encode object surfaces is proposed. This function varies smoothly across surfaces and hence can be accurately reconstructed from sampled data. The zero value iso surface of the distance map yields the object surface and the derivative of the distance map yields the surface normal. Examples of rendered images are presented along with a new method for calculating distance maps from sampled binary data.
{"title":"Using distance maps for accurate surface representation in sampled volumes","authors":"S. Gibson","doi":"10.1145/288126.288142","DOIUrl":"https://doi.org/10.1145/288126.288142","url":null,"abstract":"High quality rendering and physics based modeling in volume graphics have been limited because intensity based volumetric data do not represent surfaces well. High spatial frequencies due to abrupt intensity changes at object surfaces result in jagged or terraced surfaces in rendered images. The use of a distance-to-closest-surface function to encode object surfaces is proposed. This function varies smoothly across surfaces and hence can be accurately reconstructed from sampled data. The zero value iso surface of the distance map yields the object surface and the derivative of the distance map yields the surface normal. Examples of rendered images are presented along with a new method for calculating distance maps from sampled binary data.","PeriodicalId":167141,"journal":{"name":"IEEE Symposium on Volume Visualization (Cat. No.989EX300)","volume":"59 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":"127033775","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}
The process of generating discrete surfaces in a volumetric representation, termed voxelization, is confronted with topological considerations as well as accuracy and efficiency requirements. The authors introduce a new method for voxelizing planar objects which, unlike existing methods, provides topological conformity through geometric measures. They extend their approach to provide, for the first time, an accurate and coherent method for voxelizing polygon meshes. This method eliminates common voxelization artifacts at edges and vertices. They prove the method's topological attributes and report performance of their implementation. Finally, they demonstrate that this approach forms a basis for a new set of voxelization algorithms by voxelizing an example cubic object.
{"title":"An accurate method for voxelizing polygon meshes","authors":"Jian Huang, R. Yagel, V. Filippov, Y. Kurzion","doi":"10.1145/288126.288181","DOIUrl":"https://doi.org/10.1145/288126.288181","url":null,"abstract":"The process of generating discrete surfaces in a volumetric representation, termed voxelization, is confronted with topological considerations as well as accuracy and efficiency requirements. The authors introduce a new method for voxelizing planar objects which, unlike existing methods, provides topological conformity through geometric measures. They extend their approach to provide, for the first time, an accurate and coherent method for voxelizing polygon meshes. This method eliminates common voxelization artifacts at edges and vertices. They prove the method's topological attributes and report performance of their implementation. Finally, they demonstrate that this approach forms a basis for a new set of voxelization algorithms by voxelizing an example cubic object.","PeriodicalId":167141,"journal":{"name":"IEEE Symposium on Volume Visualization (Cat. No.989EX300)","volume":"70 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":"123036960","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}
Isosurfaces are an important tool for finding features in 3D scalar data. The paper describes how recursive contour meshing is applied to extract similar features in 4-dimensional space. In the case of time-varying isosurfaces f(x, y, z, t)=c, the technique constructs a solid mesh for the isosurface that sweeps a volume in space-time. An instance of an isosurface at a particular time results from applying a second constraint against this volume. The envelope defined by the time-varying isosurface can be captured in a similar way: when a time-varying isosurface f=c reaches is maximum extent, the function's partial derivative with respect to time must be zero. This second constraint and produces a surface containing the extrema of the isosurfaces. Multi-resolution models and inter-penetrating blobby objects can also be extracted from 4-dimensional representations.
等值面是寻找三维标量数据特征的重要工具。本文描述了递归轮廓网格在四维空间中提取相似特征的方法。在时变等值面f(x, y, z, t)=c的情况下，该技术为在时空中扫描体积的等值面构建了一个实体网格。在特定时间的等值面实例是通过对该体积施加第二个约束而产生的。时变等值面定义的包络线可以用类似的方式捕获:当时变等值面f=c达到最大值时，函数对时间的偏导数必须为零。这第二个约束产生一个包含等值面的极值的曲面。从四维表示中也可以提取出多分辨率模型和互穿透的斑点状物体。
{"title":"Extracting iso-valued features in 4-dimensional scalar fields","authors":"C. Weigle, D. Banks","doi":"10.1145/288126.288175","DOIUrl":"https://doi.org/10.1145/288126.288175","url":null,"abstract":"Isosurfaces are an important tool for finding features in 3D scalar data. The paper describes how recursive contour meshing is applied to extract similar features in 4-dimensional space. In the case of time-varying isosurfaces f(x, y, z, t)=c, the technique constructs a solid mesh for the isosurface that sweeps a volume in space-time. An instance of an isosurface at a particular time results from applying a second constraint against this volume. The envelope defined by the time-varying isosurface can be captured in a similar way: when a time-varying isosurface f=c reaches is maximum extent, the function's partial derivative with respect to time must be zero. This second constraint and produces a surface containing the extrema of the isosurfaces. Multi-resolution models and inter-penetrating blobby objects can also be extracted from 4-dimensional representations.","PeriodicalId":167141,"journal":{"name":"IEEE Symposium on Volume Visualization (Cat. No.989EX300)","volume":"8 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":"124850414","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}
The authors present a method for adaptive interpolation, to be used with any volume rendering algorithm, which provides high image quality while diminishing considerably the computation time. The method uses the projection details of the wavelet transform of the sampled data to obtain a local estimate of the spectral content of the data. Whenever the function (sampled data) approximates a polynomial of order less than or equal to the moments of the wavelet, the details are zero or near zero. This property is wed to identify constant, linear and non-linear zones within the data in order to choose the appropriate interpolation filter during rendering time.
{"title":"Wavelet based adaptive interpolation for volume rendering","authors":"Ricardo Sánchez, Marcelo Carvajal","doi":"10.1145/288126.288183","DOIUrl":"https://doi.org/10.1145/288126.288183","url":null,"abstract":"The authors present a method for adaptive interpolation, to be used with any volume rendering algorithm, which provides high image quality while diminishing considerably the computation time. The method uses the projection details of the wavelet transform of the sampled data to obtain a local estimate of the spectral content of the data. Whenever the function (sampled data) approximates a polynomial of order less than or equal to the moments of the wavelet, the details are zero or near zero. This property is wed to identify constant, linear and non-linear zones within the data in order to choose the appropriate interpolation filter during rendering time.","PeriodicalId":167141,"journal":{"name":"IEEE Symposium on Volume Visualization (Cat. No.989EX300)","volume":"24 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":"127831777","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}
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. A data structure we term the histogram volume captures the relationship between these quantities throughout the volume in a position independent, computationally efficient fashion. We describe the theoretical importance of the quantities measured by the histogram volume, the implementation issues in its calculation, and a method for semiautomatic transfer function generation through its analysis. We conclude with results of the method on both idealized synthetic data as well as real world datasets.
{"title":"Semi-automatic generation of transfer functions for direct volume rendering","authors":"G. Kindlmann, James W. Durkin","doi":"10.1145/288126.288167","DOIUrl":"https://doi.org/10.1145/288126.288167","url":null,"abstract":"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. A data structure we term the histogram volume captures the relationship between these quantities throughout the volume in a position independent, computationally efficient fashion. We describe the theoretical importance of the quantities measured by the histogram volume, the implementation issues in its calculation, and a method for semiautomatic transfer function generation through its analysis. We conclude with results of the method on both idealized synthetic data as well as real world datasets.","PeriodicalId":167141,"journal":{"name":"IEEE Symposium on Volume Visualization (Cat. No.989EX300)","volume":"37 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":"121678858","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}
C. Bajaj, Valerio Pascucci, G. Rabbiolo, D. Schikorc
Hypervolume visualization is designed to provide simple and fully explanatory images that give comprehensive in-sights into the global structure of scalar fields of any dimension. The basic idea is to have a dimension independent viewing system that scales nicely with the geometric dimension of the dataset and that can be combined with classical approaches like isocontouring and animation of slices of nD data. One completely abandons (for core simplicity) rendering techniques, such as hidden surface removal or lighting or radiosity, that enhance three dimensional realism and concentrate on the real-time display of images that highlight structural (topological) features of the no dataset (holes, tunnels, cavities, depressions, extrema, etc.). Hypervolume visualization on the one hand is a generalization of direct parallel projection methods in volume rendering. To achieve efficiency (and real-time performance on a graphics workstation) the authors combine the advantages of (i) a hierarchical representations of the hypervolume data for multiresolution display and (ii) generalized object space splatting combined with texture-mapped graphics hardware acceleration. The main results of the paper are thus both a multiresolution direct rendering algorithm and scalable graphical user interface that provides global views of scalar fields in any dimension, while maintaining the fundamental characteristics of ease of use, and quick exploratory user interaction.
{"title":"Hypervolume visualization: a challenge in simplicity","authors":"C. Bajaj, Valerio Pascucci, G. Rabbiolo, D. Schikorc","doi":"10.1145/288126.288173","DOIUrl":"https://doi.org/10.1145/288126.288173","url":null,"abstract":"Hypervolume visualization is designed to provide simple and fully explanatory images that give comprehensive in-sights into the global structure of scalar fields of any dimension. The basic idea is to have a dimension independent viewing system that scales nicely with the geometric dimension of the dataset and that can be combined with classical approaches like isocontouring and animation of slices of nD data. One completely abandons (for core simplicity) rendering techniques, such as hidden surface removal or lighting or radiosity, that enhance three dimensional realism and concentrate on the real-time display of images that highlight structural (topological) features of the no dataset (holes, tunnels, cavities, depressions, extrema, etc.). Hypervolume visualization on the one hand is a generalization of direct parallel projection methods in volume rendering. To achieve efficiency (and real-time performance on a graphics workstation) the authors combine the advantages of (i) a hierarchical representations of the hypervolume data for multiresolution display and (ii) generalized object space splatting combined with texture-mapped graphics hardware acceleration. The main results of the paper are thus both a multiresolution direct rendering algorithm and scalable graphical user interface that provides global views of scalar fields in any dimension, while maintaining the fundamental characteristics of ease of use, and quick exploratory user interaction.","PeriodicalId":167141,"journal":{"name":"IEEE Symposium on Volume Visualization (Cat. No.989EX300)","volume":"11 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":"124297746","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}
The authors analyze different filters used for the voxelization of analytically described objects. They show that, when the voxel model is used for visualization, the filter design is related to the subsequent rendering phase, namely the gradient estimation technique. The theoretical and experimental analyses show that, in order to avoid a systematic error in normal estimation, the density profile near the surface should be linearly proportional to the distance from the surface. Optimal thickness of this transient region has been estimated to be about 3 voxel units. Based on these results, they propose a technique for voxelization of arbitrary parametric surfaces, using a hierarchical subdivision of the 2D surface domain.
{"title":"Object voxelization by filtering","authors":"M. Srámek, A. Kaufman","doi":"10.1109/SVV.1998.729592","DOIUrl":"https://doi.org/10.1109/SVV.1998.729592","url":null,"abstract":"The authors analyze different filters used for the voxelization of analytically described objects. They show that, when the voxel model is used for visualization, the filter design is related to the subsequent rendering phase, namely the gradient estimation technique. The theoretical and experimental analyses show that, in order to avoid a systematic error in normal estimation, the density profile near the surface should be linearly proportional to the distance from the surface. Optimal thickness of this transient region has been estimated to be about 3 voxel units. Based on these results, they propose a technique for voxelization of arbitrary parametric surfaces, using a hierarchical subdivision of the 2D surface domain.","PeriodicalId":167141,"journal":{"name":"IEEE Symposium on Volume Visualization (Cat. No.989EX300)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134325568","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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