STATISTICAL COMPUTATION OF SALIENT ISO-VALUES

Tenginakai, Shivaraj; Machiraju, Raghu

STATISTICAL COMPUTATION OF SALIENT ISO-VALUES

Files

019-024.pdf (275.85 KB)

Date

2002

Authors

Tenginakai, Shivaraj
Machiraju, Raghu

Publisher

The Eurographics Association

Abstract

Detection of the salient iso-values in a volume dataset is often the first step towards its exploration. An error-and-trail approach is often used; new semi-automatic techniques either make assumptions about their data [4] or present multiple criteria for analysis. Determining if a dataset satisfies an algorithm s assumptions, or the criteria to be used in an analysis are both non-trivial tasks. The use of a dataset s statistical signatures, local higher order moments (LHOMs), to characterize its salient iso-values was presented in [10]. In this paper we propose a computational algorithm that uses LHOMs for expedient estimation of salient iso-values. As LHOMs are model independent statistical signatures our algorithm does not impose any assumptions on the data. Further, the algorithm has a single criterion for characterization of the salient iso-values, and the search for this criterion is easily automated. Examples from medical and computational domains are used to demonstrate the effectiveness of the proposed algorithm.

        @inproceedings{:10.2312/VisSym/VisSym02/019-024
,
booktitle = {Eurographics / IEEE VGTC Symposium on Visualization
},
editor = {D. Ebert and P. Brunet and I. Navazo
},
title = {{STATISTICAL COMPUTATION OF SALIENT ISO-VALUES
}},
author = {Tenginakai, Shivaraj and 
Machiraju, Raghu
},
year = {2002
},
publisher = {The Eurographics Association
},
ISSN = {1727-5296
},
ISBN = {1-58113-536-X
},
DOI = {/10.2312/VisSym/VisSym02/019-024
}
}