Interactive Position-dependent Customization of Transfer Function Classification Parameters in Volume Rendering

Brix Tobias, Scherzinger Aaron, Völker Andreas, Hinrichs Klaus

Research article in edited proceedings (conference) | Peer reviewed

Abstract

In direct volume rendering (DVR) and related techniques a basic operation is the classification of data values by mapping (mostly scalar) intensities to color values using a transfer function. However, in some cases this kind of mapping might not suffice to achieve satisfying rendering results, for instance when intensity homogeneities occur in the volume data due to technical restrictions of the scanner technology. In this case it might be desirable to customize one or more parameters of the visualization depending on the position within the volume. In this paper we propose a novel approach for an interactive position-dependent customization of arbitrary parameters of the transfer function classification. Our method can easily be integrated into existing volume rendering pipelines by incorporating an additional operation during the classification step. It allows the user to interactively modify the rendering result by specifying reference points within the data set and customizing their associated visualization parameters while receiving direct visual feedback. Since the additional memory requirements of our method do not depend on the size of the visualized data our approach is applicable to large data sets, for instance in the field of ultra microscopy.

Details about the publication

Page range83-92
StatusPublished
Release year2015
Language in which the publication is writtenEnglish
ConferenceEurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2015, Chester, England, undefined

Authors from the University of Münster

Brix, Tobias
Professorship for applied computer science
Hinrichs, Klaus
Professorship for applied computer science
Scherzinger, Aaron
Professorship for applied computer science
Völker, Andreas
Professorship for applied computer science