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18 January 2010 Multichannel transfer function with dimensionality reduction
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Proceedings Volume 7530, Visualization and Data Analysis 2010; 75300A (2010) https://doi.org/10.1117/12.839526
Event: IS&T/SPIE Electronic Imaging, 2010, San Jose, California, United States
Abstract
The design of transfer functions for volume rendering is a difficult task. This is particularly true for multichannel data sets, where multiple data values exist for each voxel. In this paper, we propose a new method for transfer function design. Our new method provides a framework to combine multiple approaches and pushes the boundary of gradient-based transfer functions to multiple channels, while still keeping the dimensionality of transfer functions to a manageable level, i.e., a maximum of three dimensions, which can be displayed visually in a straightforward way. Our approach utilizes channel intensity, gradient, curvature and texture properties of each voxel. The high-dimensional data of the domain is reduced by applying recently developed nonlinear dimensionality reduction algorithms. In this paper, we used Isomap as well as a traditional algorithm, Principle Component Analysis (PCA). Our results show that these dimensionality reduction algorithms significantly improve the transfer function design process without compromising visualization accuracy. In this publication we report on the impact of the dimensionality reduction algorithms on transfer function design for confocal microscopy data.
© (2010) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Han Suk Kim, Jürgen P. Schulze, Angela C. Cone, Gina E. Sosinsky, and Maryann E. Martone "Multichannel transfer function with dimensionality reduction", Proc. SPIE 7530, Visualization and Data Analysis 2010, 75300A (18 January 2010); https://doi.org/10.1117/12.839526
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