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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Orthogonal subspace projection (OSP) has been successfully applied to hyperspectral imageprocessing. In order for OSP to be effective, the number of bands must be no less than that of signatures to be classified so t...
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We present a new algorithm based on Dual Graph Contraction (DGC) to transform the Run Graph into its Minimum Line Property Preserving (MLPP) form which, when implemented in parallel, requires O(log(longestcurve)) step...
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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 execution time estimation of programs plays an important role in parallelizing compilers. In this paper, we preseni a recursive approach aimed at predicating lower bounds on the minimum times taken to execute prog...
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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.
We present a general method of constructing global function fields with many rational places based on Drinfeld modules of rank 1 and narrow ray class fields. This method leads to many improvements on previous construc...
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In this paper, we investigate the application of a representation for tomographic similarity to recognize vessels in aortic flow images. Due to the strict acquisition protocol, the spatial embedding of different vesse...
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In this paper, we investigate the application of a representation for tomographic similarity to recognize vessels in aortic flow images. Due to the strict acquisition protocol, the spatial embedding of different vessels in aortic flow images is largely similar for different subjects. By modeling the vessel embedding of these images by means of Voronoi arrangements, the spatial arrangement of a 'training' image can be utilized to label unknown objects in target images by matching their arrangements. The arrangement matching method was tested on routinely acquired flow images of 12 subjects, in which four major vessels were drawn manually. In all cases, the arrangement matching labeled the vessels in the images correctly, though clear anatomic differences in size and shape were present. This shows that the arrangement metric is a powerful representation of the content of images, in which objects differ in size, shape and location, but of which the spatial embedding is similar.
A signal-to-noise ratio based PCA approach, called maximum noise fraction (MNF) transformation or noise adjusted principal components (NAPC) transform PCA was previously developed to arrange principal components in de...
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ISBN:
(纸本)0780344030
A signal-to-noise ratio based PCA approach, called maximum noise fraction (MNF) transformation or noise adjusted principal components (NAPC) transform PCA was previously developed to arrange principal components in decreasing order of image quality rather than data variance as done for PCA. One of major disadvantages of this approach is that the noise covariance matrix must be estimated accurately from the data a priori. Another is that the factor of interference is not taken into account in MNF or NAPC where the effect of interference tends to be more serious than noise in hyperspectral images. In this paper, these two problems are addressed by considering the interference as a separate unwanted signal source from which an interference rejection approach to noise adjusted principal components transform (IRNAPC) can be developed in a similar manner that the NAPC was derived. It is shown that if interference is taken care of properly, IRNAPC significantly improves NAPC. Additionally, interference annihilation also improves the estimation of the noise covariance matrix.
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