Title
Fast volumetric data exploration with importance-based accumulated transparency modulation
Abstract
Direct volume rendering techniques have been successfully applied to visualizing volumetric datasets across many application domains. Due to the sensitivity of transfer functions and the complexity of fine-tuning transfer functions, direct volume rendering is still not widely used in practice. For fast volumetric data exploration, we propose Importance-Based Accumulated Transparency Modulation which does not rely on transfer function manipulation. This novel rendering algorithm is a generalization and extension of the Maximum Intensity Difference Accumulation technique. By only modifying the accumulated transparency, the resulted volume renderings are essentially high dynamic range. We show that by using several common importance measures, different features of the volumetric datasets can be highlighted. The results can be easily extended to a high-dimensional importance difference space, by mixing the results from an arbitrary number of importance measures with weighting factors, which all control the final output with a monotonic behavior. With Importance-Based Accumulated Transparency Modulation, the end-user can explore a wide variety of volumetric datasets quickly without the burden of manually setting and adjusting a transfer function.
Year
DOI
Venue
2010
10.2312/VG/VG10/061-068
Volume Graphics 2007
Keywords
Field
DocType
transparency modulation,direct volume rendering technique,visualizing volumetric datasets,fine-tuning transfer function,transfer function,high-dimensional importance difference space,transfer function manipulation,direct volume rendering,fast volumetric data exploration,common importance measure,volumetric datasets
Monotonic function,Transparency (graphic),Computer vision,Volume rendering,Weighting,Computer science,Modulation,Transfer function,Artificial intelligence,Rendering (computer graphics),High dynamic range
Conference
Citations 
PageRank 
References 
1
0.35
20
Authors
2
Name
Order
Citations
PageRank
Y Wan1274.28
C Hansen230644.56