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Penny Rheingans, David Ebert, "Volume Illustration: Nonphotorealistic Rendering of Volume Models," IEEE Transactions on Visualization and Computer Graphics, vol. 7, no. 3, pp. 253264, JulySeptember, 2001.  
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@article{ 10.1109/2945.942693, author = {Penny Rheingans and David Ebert}, title = {Volume Illustration: Nonphotorealistic Rendering of Volume Models}, journal ={IEEE Transactions on Visualization and Computer Graphics}, volume = {7}, number = {3}, issn = {10772626}, year = {2001}, pages = {253264}, doi = {http://doi.ieeecomputersociety.org/10.1109/2945.942693}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
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TY  JOUR JO  IEEE Transactions on Visualization and Computer Graphics TI  Volume Illustration: Nonphotorealistic Rendering of Volume Models IS  3 SN  10772626 SP253 EP264 EPD  253264 A1  Penny Rheingans, A1  David Ebert, PY  2001 KW  Volume rendering KW  nonphotorealistic rendering KW  illustration KW  lighting models KW  shading KW  transfer functions KW  visualization. VL  7 JA  IEEE Transactions on Visualization and Computer Graphics ER   
Abstract—Accurately and automatically conveying the structure of a volume model is a problem not fully solved by existing volume rendering approaches. Physicsbased volume rendering approaches create images which may match the appearance of translucent materials in nature, but may not embody important structural details. Transfer function approaches allow flexible design of the volume appearance, but generally require substantial hand tuning for each new data set in order to be effective. We introduce the volume illustration approach, combining the familiarity of a physicsbased illumination model with the ability to enhance important features using nonphotorealistic rendering techniques. Since features to be enhanced are defined on the basis of local volume characteristics rather than volume sample value, the application of volume illustration techniques requires less manual tuning than the design of a good transfer function. Volume illustration provides a flexible unified framework for enhancing structural perception of volume models through the amplification of features and the addition of illumination effects.
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