We present a method for the hierarchical representation of vector fields. Our approach is based on iterative refinement using clustering and principal component analysis. The input to our algorithm is a discrete set o...
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ISBN:
(纸本)9780780358973
We present a method for the hierarchical representation of vector fields. Our approach is based on iterative refinement using clustering and principal component analysis. The input to our algorithm is a discrete set of points with associated vectors. The algorithm generates a top-down segmentation of the discrete field by splitting clusters of points. We measure the error of the various approximation levels by measuring the discrepancy between streamlines generated by the original discrete field and its approximations based on much smaller discrete data sets. Our method assumes no particular structure of the field, nor does it require any topological connectivity information. It is possible to generate multiresolution representations of vector fields using this approach.
Presents a method for the hierarchical representation of vector fields. Our approach is based on iterative refinement using clustering and principal component analysis. The input to our algorithm is a discrete set of ...
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Presents a method for the hierarchical representation of vector fields. Our approach is based on iterative refinement using clustering and principal component analysis. The input to our algorithm is a discrete set of points with associated vectors. The algorithm generates a top-down segmentation of the discrete field by splitting clusters of points. We measure the error of the various approximation levels by measuring the discrepancy between streamlines generated by the original discrete field and its approximations based on much smaller discrete data sets. Our method assumes no particular structure of the field, nor does it require any topological connectivity information. It is possible to generate multi-resolution representations of vector fields using this approach.
We present a new technique for surface reconstruction of digitized models in three dimensions. Concerning this problem, we are given a data set in three-dimensional space, represented as a set of points without connec...
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We present a new technique for surface reconstruction of digitized models in three dimensions. Concerning this problem, we are given a data set in three-dimensional space, represented as a set of points without connectivity information, and the goal is to find, for a fixed number of vertices, a set of approximating triangles which minimize the error measured by the displacement from the given points. Our method creates near-optimal linear spline approximations, using an iterative optimization scheme based on simulated annealing. The algorithm adopts the mesh to the data set and moves the triangles to enhance feature lines. At the end, we can use the approach to create a hierarchy of different resolutions for the model.
Animation and visualization of rectilinear data require interpolation schemes for smooth image generation. Piecewise trilinear interpolation, the de facto standard for interpolating rectilinear data, usually leads to ...
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We present a method for the construction of multiple levels of tetrahedral meshes approximating a trivariate function at different levels of detail. Starting with an initial, high-resolution triangulation of a three-d...
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We present a method for the construction of multiple levels of tetrahedral meshes approximating a trivariate function at different levels of detail. Starting with an initial, high-resolution triangulation of a three-dimensional region, we construct coarser representation levels by collapsing tetrahedra. Each triangulation defines a linear spline function, where the function values associated with the vertices are the spline coefficients. Based on predicted errors, we collapse tetrahedron in the grid that do not cause the maximum error to exceed a use-specified threshold. Bounds are stored for individual tetrahedra and are updated as the mesh is simplified. We continue the simplification process until a certain error is reached. The result is a hierarchical data description suited for the efficient visualization of large data sets at varying levels of detail.
The authors investigate methods by which successive approximations to a sphere can be generated from polyhedra. Each approximation can be obtained by bevel-cutting each edge of the previous approximation with a plane ...
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ISBN:
(纸本)9780818684456
The authors investigate methods by which successive approximations to a sphere can be generated from polyhedra. Each approximation can be obtained by bevel-cutting each edge of the previous approximation with a plane tangent to the sphere. They show that each member of the sequence of polyhedra can be associated with a Voronoi tessellation of the sphere. Under this formulation, the bevel-cutting operation can be defined by the insertion of points into the Voronoi tessellation. The algorithm is defined such that affine combinations of the polyhedra will converge to affine operations of the sphere. The method is useful as a modeling operation and as a level-of-detail representation for a sphere.
作者:
Gary E. FordAdel I. El-FallahCIPIC
Center for Image Processing and Integrated Computing University of California Davis Davis CA 95616
Most of the recent work on inhomogeneous diffusion in image filtering focuses on diffusing the isotope curve. We present a less familiar approach to the development of inhomogeneous diffusion algorithms in which the i...
作者:
Ford, GEElFallah, AICIPIC
Center for Image Processing and Integrated Computing University of California Davis Davis CA 95616
Most of the recent work on inhomogeneous diffusion in image filtering focuses on diffusing the isotope curve. We present a less familiar approach to the development of inhomogeneous diffusion algorithms in which the i...
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Most of the recent work on inhomogeneous diffusion in image filtering focuses on diffusing the isotope curve. We present a less familiar approach to the development of inhomogeneous diffusion algorithms in which the image is regarded as a surface in three-space. The magnitude of the surface normal controls a diffusion that evolves the image surface at a speed proportional to its mean curvature. A discrete algorithm to implement this proposed diffusion is introduced, and we show experimentally that the algorithm develops singularities that reveal, preserve, and enhance the underlying signal. If the input signal is an isolated noisy edge, this leads to complete noise removal and enhancement without affecting the edge locality. (C) 1997 John Wiley & Sons, Inc.
In recent work, we have examined the performance of wavelet coders using a perceptually relevant image quality metric, the Picture Quality Scale (PQS). In that study, we considered some of the design options available...
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ISBN:
(纸本)0819424366
In recent work, we have examined the performance of wavelet coders using a perceptually relevant image quality metric, the Picture Quality Scale (PQS). In that study, we considered some of the design options available with respect to choice of wavelet basis, quantizer, and method for error-free encoding of the quantized coefficients, including the EZW methodology. A specific combination of these design options provides the best trade off between performance and PQS quality. Here, we extend this comparison by evaluating the performance of JPEG and the previously chosen optimal wavelet scheme, focusing principally on the high quality range.
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