Gradient Estimation in Volume Data using 4D Linear Regression
Loading...
Date
2000
Journal Title
Journal ISSN
Volume Title
Publisher
Blackwell Publishers Ltd and the Eurographics Association
Abstract
In this paper a new gradient estimation method is presented which is based on linear regression. Previous contextual shading techniques try to fit an approximate function to a set of surface points in the neighborhood of a given voxel. Therefore a system of linear equations has to be solved using the computationally expensive Gaussian elimination. In contrast, our method approximates the density function itself in a local neighborhood with a 3D regression hyperplane. This approach also leads to a system of linear equations but we will show that it can be solved with an efficient convolution. Our method provides at each voxel location the normal vector and the translation of the regression hyperplane which are considered as a gradient and a filtered density value respectively. Therefore this technique can be used for surface smoothing and gradient estimation at the same time.
Description
@article{10.1111:1467-8659.00427,
journal = {Computer Graphics Forum},
title = {{Gradient Estimation in Volume Data using 4D Linear Regression}},
author = {Neumann, Laszlo and Csebfalvi, Balazs and Konig, Andreas and Groller, Eduard},
year = {2000},
publisher = {Blackwell Publishers Ltd and the Eurographics Association},
ISSN = {1467-8659},
DOI = {10.1111/1467-8659.00427}
}