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Publication Type	technical report
School or College	College of Engineering
Department	Computing, School of
Creator	Mehta, Mihir
Title	Matte volumes for selective data visualization
Date	1995-08
Description	The matte volumes system uses a volume renderer, surface renderer, and slice viewer for the exploration and visualization of three-dimensional scalar field data. The size and complexity of the volume data pose an interesting challenge to the ideal of providing the scientist with a system which automatically focuses on regions of interest and accurately visualizes the data from any angle in real time. Matte volumes take a step in the direction by providing the scientist with tools for exploring the data and focusing on regions of interest. Matte volumes are a way of specifying the regions of interest.
Type	Text
Publisher	University of Utah
Subject	matte volumes; three-dimensional scalar field data; computers; matte volumes system
Subject LCSH	Computer graphics; Computer vision; Imaging systems in medicine
Language	eng
Bibliographic Citation	Mehta, M. (1995). Matte volumes for selective data visualization.
Series	University of Utah Computer Science Technical Report
Relation is Part of	ARPANET
Format Medium	application/pdf
Format Extent	158,804 Bytes
File Name	Mehta-Matte_Volumes.pdf
Conversion Specifications	Original scanned with Kirtas 2400 and saved as 400 ppi uncompressed TIFF. PDF generated by Adobe Acrobat Pro X for CONTENTdm display
ARK	ark:/87278/s6418x43
Setname	ir_computersa
ID	93441
Reference URL	https://collections.lib.utah.edu/ark:/87278/s6418x43

Page Metadata

Title	Page 55
Setname	ir_computersa
ID	93438
OCR Text	Show 46 [27] Kwan-Liu Ma, Michael Cohen, and James Painter. Volume seeds: A volume exploration technique. The Journal of Visualization and Computer Animation, 2, 1991. [28] James V. Miller, David E. Breen, William E. Lorensen, Robert M. O'Bara, and Michael J. Wozny. Geometrically deformed models: A method for extracting closed geometric models from volume data. Computer Graphics (SIGGRAPH '91 Proceedings), 25( 4):217-226, July 1991. [29] M. Nagao and T. Matsuyama. Edge preserving smoothing. Computer Graphics and Image Processing, 9:394-407, 1979. [30] P.M. Narendra. A seperable median filter for image noise smoothing. In Proceedings of the IEEE Conference on Pattern Recognition and Image Processing, pages 137-141, 1978. [31] P. Perona and J. Malik. Scale space and edge detection using anisotropic diffusion. In Proceedings of the IEEE Workshop on Computer Vision, pages 16-22, Miami, FL, November 1987. [32] T. Porter and T. Duff. Compositing digital images. Computer Graphics (Proceedings of SIGGRAPH 1984), 18(3):253-259, July 1984. [33] P. Sabella. A rendering algorithm for visualizing 3D scalar fields. Computer Graphics (Proceedings of SIGGRAPH 1988}, 22( 4):51-58, August 1988. [34] Philippe Saint-Marc, Jer-Sen Chen, and Gerard Medioni. Adaptive smoothing: A general tool for early vision. IEEE Transactions on Pattern Analysis and Machine Intelligence, 13(6):514-529, June 1991. [35] Alvy Ray Smith. Tint fill. Computer Graphics (Proceedings of SIGGRAPH 1979), 13(2) :276-283, August 1979. [36] F. Tomita and S. Tsuji. Extraction of multiple regions by smoothing in selected neighborhoods. IEEE Transactions on System, Man and Cybernetics, 7:107- 109, 1977. [37] H.K. Tuy and L.T. Tuy. Direct 2D display of 3D objects. IEEE Computer Graphics and Applications, 4(10) :29-33, October 1984. [38] C Upson, editor. Chapel Hill Workshop on Volume Visualization, Conference Proceedings, May 1989. [39] C. Upson and M. Keeler. V-buffer: Visible volume rendering. Computer Graphics (Proceedings of SIGGRAPH 1988), ·22(4):59-64, August 1988. [40] D.C.C. Wang, A.H. Vagnucci, and C.C. Li. Gradient inverse weighted smoothing scheme and the evaluation of its performance. Computer Graphics and Image Processing, 15:167-181, 1981.
Reference URL	https://collections.lib.utah.edu/ark:/87278/s6418x43/93438