Interactive Transfer Function Design Based on Editing Direct Volume Rendered Images

Direct volume rendered images (DVRIs) have been widely used to reveal structures in volumetric data. However, DVRIs generated by many volume visualization techniques can only partially satisfy users' demands. In this paper, we propose a framework for editing DVRIs, which can also be used for interactive transfer function (TF) design. Our approach allows users to fuse multiple features in distinct DVRIs into a comprehensive one, to blend two DVRIs, and/or to delete features in a DVRI. We further present how these editing operations can generate smooth animations for focus + context visualization. Experimental results on some real volumetric data demonstrate the effectiveness of our method.

[1]  Hanspeter Pfister,et al.  Generation of transfer functions with stochastic search techniques , 1996, Proceedings of Seventh Annual IEEE Visualization '96.

[2]  Eduard Gröller,et al.  Mastering Transfer Function Specification by using VolumePro Technology , 2000 .

[3]  Alastair R. Allen,et al.  A Similarity Metric for Edge Images , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[4]  William J. Schroeder,et al.  The Visualization Toolkit , 2005, The Visualization Handbook.

[5]  Deborah Silver,et al.  Dataset traversal with motion-controlled transfer functions , 2005, VIS 05. IEEE Visualization, 2005..

[6]  Dorothea Heiss-Czedik,et al.  An Introduction to Genetic Algorithms. , 1997, Artificial Life.

[7]  M WellsWilliam,et al.  Alignment by Maximization of Mutual Information , 1997 .

[8]  Min Chen,et al.  Comparative evaluation of visualization and experimental results using image comparison metrics , 2002, IEEE Visualization, 2002. VIS 2002..

[9]  Amitava Datta,et al.  A parallel coordinates style interface for exploratory volume visualization , 2005, IEEE Transactions on Visualization and Computer Graphics.

[10]  Ivan Viola,et al.  Importance-driven feature enhancement in volume visualization , 2005, IEEE Transactions on Visualization and Computer Graphics.

[11]  Donald H. House,et al.  On the optimization of visualizations of complex phenomena , 2005, VIS 05. IEEE Visualization, 2005..

[12]  Zhou Wang,et al.  Why is image quality assessment so difficult? , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[13]  Jeffrey Lubin,et al.  A VISUAL DISCRIMINATION MODEL FOR IMAGING SYSTEM DESIGN AND EVALUATION , 1995 .

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

[15]  Hong Zhou,et al.  Fusing Features in Direct Volume Rendered Images , 2006, ISVC.

[16]  Ivan Viola,et al.  Caricaturistic Visualization , 2006, IEEE Transactions on Visualization and Computer Graphics.

[17]  Hong Zhou,et al.  Viewpoint Selection for Angiographic Volume , 2006, ISVC.

[18]  Yuriko Takeshima,et al.  A feature-driven approach to locating optimal viewpoints for volume visualization , 2005, VIS 05. IEEE Visualization, 2005..

[19]  Thomas Ertl,et al.  Interactive Clipping Techniques for Texture-Based Volume Visualization and Volume Shading , 2003, IEEE Trans. Vis. Comput. Graph..

[20]  Stefan Bruckner,et al.  Exploded Views for Volume Data , 2006, IEEE Transactions on Visualization and Computer Graphics.

[21]  Zesheng Tang,et al.  A Perceptual Framework for Comparisons of Direct Volume Rendered Images , 2006, PSIVT.

[22]  K. Dejong,et al.  An analysis of the behavior of a class of genetic adaptive systems , 1975 .

[23]  Daniel Weiskopf,et al.  On the role of color in the perception of motion in animated visualizations , 2004, IEEE Visualization 2004.

[24]  William S. Robinson,et al.  Understanding Phenomenal Consciousness , 2004 .

[25]  William A. Barrett,et al.  Intelligent scissors for image composition , 1995, SIGGRAPH.

[26]  Harry Shum,et al.  Lazy snapping , 2004, ACM Trans. Graph..

[27]  G. W. Furnas,et al.  Generalized fisheye views , 1986, CHI '86.

[28]  Kwan-Liu Ma,et al.  Using Motion to Illustrate Static 3D Shape--Kinetic Visualization , 2003, IEEE Trans. Vis. Comput. Graph..

[29]  Andrew S. Winter,et al.  Spatial transfer functions: a unified approach to specifying deformation in volume modeling and animation , 2003, VG.

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

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

[32]  Gary W. Meyer,et al.  Comparison of two image quality models , 1998, Electronic Imaging.

[33]  Carl Gutwin,et al.  Multiblending: displaying overlapping windows simultaneously without the drawbacks of alpha blending , 2004, CHI.

[34]  Paul A. Viola,et al.  Alignment by Maximization of Mutual Information , 1997, International Journal of Computer Vision.

[35]  Kwan-Liu Ma,et al.  Interactive multi-scale exploration for volume classification , 2006, The Visual Computer.

[36]  Anna Vilanova,et al.  Visualization of boundaries in volumetric data sets using LH histograms , 2006, IEEE Transactions on Visualization and Computer Graphics.

[37]  Min Chen,et al.  Feature Aligned Volume Manipulation for Illustration and Visualization , 2006, IEEE Transactions on Visualization and Computer Graphics.

[38]  Kwan-Liu Ma Image Graps- A Novel Interface for Visual Data Exploration , 1999 .

[39]  Deepak R. Kenchammana-Hosekote,et al.  Volume animation using the skeleton tree , 1998, IEEE Symposium on Volume Visualization (Cat. No.989EX300).

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

[41]  Hong Zhou,et al.  Focus + Context Visualization with Animation , 2006, PSIVT.

[42]  Christopher G. Healey,et al.  Visualizing data with motion , 2005, VIS 05. IEEE Visualization, 2005..

[43]  G. Kindlmann Transfer Functions in Direct Volume Rendering : Design , Interface , Interaction , 2002 .

[44]  Paul A. Beardsley,et al.  Design galleries: a general approach to setting parameters for computer graphics and animation , 1997, SIGGRAPH.

[45]  Jens Schneider,et al.  ClearView: An Interactive Context Preserving Hotspot Visualization Technique , 2006, IEEE Transactions on Visualization and Computer Graphics.

[46]  Karl Sims,et al.  Artificial evolution for computer graphics , 1991, SIGGRAPH.

[47]  Amitabh Varshney,et al.  Saliency-guided Enhancement for Volume Visualization , 2006, IEEE Transactions on Visualization and Computer Graphics.

[48]  Klaus Mueller,et al.  The magic volume lens: an interactive focus+context technique for volume rendering , 2005, VIS 05. IEEE Visualization, 2005..

[49]  Jinho Lee The Transfer Function BakeOff , 2001 .

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

[51]  Scott J. Daly,et al.  Visible differences predictor: an algorithm for the assessment of image fidelity , 1992, Electronic Imaging.

[52]  Tien-Tsin Wong,et al.  Parallel evolutionary algorithms on graphics processing unit , 2005, 2005 IEEE Congress on Evolutionary Computation.

[53]  William E. Lorensen,et al.  The Transfer Function Bake-Off , 2001, IEEE Computer Graphics and Applications.

[54]  Joe Michael Kniss,et al.  Multidimensional Transfer Functions for Interactive Volume Rendering , 2002, IEEE Trans. Vis. Comput. Graph..