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Accurate Computation of Interval Volume Measures for Improving Histograms

  • Cuilan WangEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11844)

Abstract

The interval volume measure is defined as the volume of the space occupied by a range of isosurfaces corresponding to an interval of isovalues. The interval volume measures are very useful since they can be taken as an alternative way of producing a smooth noise-suppressing histogram. This paper proposes two new methods (i.e., the subdividing method and the slicing method) that can calculate interval volume measures with very high accuracy for scalar regular-grid volumetric datasets. It is assumed that the underlying function inside the grid cell is defined by trilinear interpolation. A refined histogram method that can produce accurate interval volume measures is also presented in the paper. All three methods are compared against one another in terms of accuracy and performance. Their improvement for computing global and local histograms is demonstrated by comparing against the previous methods.

Keywords

Isosurface Interval volume Histogram Trilinear interpolation Marching Cubes 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.School of Science and TechnologyGeorgia Gwinnett CollegeLawrencevilleUSA

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