Data Centric Transfer Functions

Data Centric Transfer Functions for High Dynamic Range Volume Data

 Credits: Amit Chourasia, Jurgen Schulze
 Tools: C++
Creating effective transfer functions for high dynamic range scalar volume data is a challenging task. For data sets with limited information about their content, deriving transfer functions using mathematical properties (gradient, curvature, etc.) is a difficult trial and error process. Using traditional method, the transfer functions are typically stored in integer look-up tables, which do not work well when the data range is large. We developed a process of opacity guidance with simple user interface that can be used as the basis for transfer function design. Our technique which uses opacity weighted histogram equalization lets users derive transfer functions for HDR floating point easily and quickly. We also showed how to adopt these techniques for real-time interactive visualization with minimal pre-processing.

Publication - Chourasia. A., Schulze. J. "Data Centric Transfer Functions for High Dynamic Range Volume Data". In Proceedings of the International Conference on Visualization and Computer Vision (WSCG) , Plzen, Czech Republic, January 29-February 01, 2007, pp. 9-16.

Oct 2006
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