Visualization Symposium, IEEE Pacific (2010)
Mar. 2, 2010 to Mar. 5, 2010
Martin Haidacher , Institute of Computer Graphics and Algorithms, Vienna University of Technology, Austria
Daniel Patel , Christian Michelsen Research, Bergen, Norway
Stefan Bruckner , Institute of Computer Graphics and Algorithms, Vienna University of Technology, Austria
Armin Kanitsar , AGFA HealthCare, Vienna, Austria
M. Eduard Groller , Institute of Computer Graphics and Algorithms, Vienna University of Technology, Austria
It is a difficult task to design transfer functions for noisy data. In traditional transfer-function spaces, data values of different materials overlap. In this paper we introduce a novel statistical transfer-function space which in the presence of noise, separates different materials in volume data sets. Our method adaptively estimates statistical properties, i.e. the mean value and the standard deviation, of the data values in the neighborhood of each sample point. These properties are used to define a transfer-function space which enables the distinction of different materials. Additionally, we present a novel approach for interacting with our new transfer-function space which enables the design of transfer functions based on statistical properties. Furthermore, we demonstrate that statistical information can be applied to enhance visual appearance in the rendering process. We compare the new method with 1D, 2D, and LH transfer functions to demonstrate its usefulness.
Transfer functions, Space technology, Computer graphics, Data visualization, Noise measurement, White noise, Medical services, Algorithm design and analysis, Rendering (computer graphics), Statistics
M. Haidacher, D. Patel, S. Bruckner, A. Kanitsar and M. E. Groller, "Volume visualization based on statistical transfer-function spaces," 2010 IEEE Pacific Visualization Symposium (PacificVis 2010)(PACIFICVIS), Taipei, 2010, pp. 17-24.