Efficient opacity specification based on feature visibilities in direct volume rendering

Due to 3D occlusion, the specification of proper opacities in direct volume rendering is a time‐consuming and unintuitive process. The visibility histograms introduced by Correa and Ma reflect the effect of occlusion by measuring the influence of each sample in the histogram to the rendered image. However, the visibility is defined on individual samples, while volume exploration focuses on conveying the spatial relationships between features. Moreover, the high computational cost and large memory requirement limits its application in multi‐dimensional transfer function design.

[1]  David S. Ebert,et al.  Structuring Feature Space: A Non-Parametric Method for Volumetric Transfer Function Generation , 2009, IEEE Transactions on Visualization and Computer Graphics.

[2]  David S. Ebert,et al.  Volume Illustration: Nonphotorealistic Rendering of Volume Models , 2001, IEEE Trans. Vis. Comput. Graph..

[3]  Kwan-Liu Ma,et al.  The Occlusion Spectrum for Volume Classification and Visualization , 2009, IEEE Transactions on Visualization and Computer Graphics.

[4]  Cüneyt Güzelis,et al.  Semiautomatic Transfer Function Initialization for Abdominal Visualization Using Self-Generating Hierarchical Radial Basis Function Networks , 2009, IEEE Transactions on Visualization and Computer Graphics.

[5]  Kwan-Liu Ma,et al.  A cluster-space visual interface for arbitrary dimensional classification of volume data , 2004, VISSYM'04.

[6]  Marc Stamminger,et al.  Spatialized Transfer Functions , 2005, EuroVis.

[7]  Boris Polyak.  The conjugate gradient method in extremal problems , 1969 .

[8]  Kwan-Liu Ma,et al.  Visibility Histograms and Visibility-Driven Transfer Functions , 2011, IEEE Transactions on Visualization and Computer Graphics.

[9]  Bernd Hamann,et al.  Topology-Controlled Volume Rendering , 2006, IEEE Transactions on Visualization and Computer Graphics.

[10]  Kwan-Liu Ma,et al.  Size-based Transfer Functions: A New Volume Exploration Technique , 2008, IEEE Transactions on Visualization and Computer Graphics.

[11]  Wei Chen,et al.  Perception-Based Transparency Optimization for Direct Volume Rendering , 2009, IEEE Transactions on Visualization and Computer Graphics.

[12]  Kwan-Liu Ma,et al.  An intelligent system approach to higher-dimensional classification of volume data , 2005, IEEE Transactions on Visualization and Computer Graphics.

[13]  Wei Chen,et al.  Volume exploration using ellipsoidal Gaussian transfer functions , 2010, 2010 IEEE Pacific Visualization Symposium (PacificVis).

[14]  Christof Rezk-Salama,et al.  High-Level User Interfaces for Transfer Function Design with Semantics , 2006, IEEE Transactions on Visualization and Computer Graphics.

[15]  Marc Levoy,et al.  Display of surfaces from volume data , 1988, IEEE Computer Graphics and Applications.

[16]  Yuriko Takeshima,et al.  Introducing topological attributes for objective-based visualization of simulated datasets , 2005, Fourth International Workshop on Volume Graphics, 2005..

[17]  David S. Ebert,et al.  Volume illustration: non-photorealistic rendering of volume models , 2000 .

[18]  Gordon L. Kindlmann,et al.  Semi-Automatic Generation of Transfer Functions for Direct Volume Rendering , 1998, VVS.

[19]  Mateu Sbert,et al.  Importance-Driven Focus of Attention , 2006, IEEE Transactions on Visualization and Computer Graphics.

[20]  Joe Michael Kniss,et al.  Interactive volume rendering using multi-dimensional transfer functions and direct manipulation widgets , 2001, Proceedings Visualization, 2001. VIS '01..

[21]  Joe Michael Kniss,et al.  Gaussian transfer functions for multi-field volume visualization , 2003, IEEE Visualization, 2003. VIS 2003..

[22]  Ross T. Whitaker,et al.  Curvature-based transfer functions for direct volume rendering: methods and applications , 2003, IEEE Visualization, 2003. VIS 2003..

[23]  Han-Wei Shen,et al.  View selection for volume rendering , 2005, VIS 05. IEEE Visualization, 2005..