Sign in
Author

Conference

Journal

Organization

Year

DOI
Look for results that meet for the following criteria:
since
equal to
before
between
and
Search in all fields of study
Limit my searches in the following fields of study
Agriculture Science
Arts & Humanities
Biology
Chemistry
Computer Science
Economics & Business
Engineering
Environmental Sciences
Geosciences
Material Science
Mathematics
Medicine
Physics
Social Science
Multidisciplinary
Keywords
(18)
Computer Graphic
Data Visualization
Extreme Point
Level Set
Materials Science
Morse Theory
Noisy Data
Optical Properties
Scientific Data
Smoothing Method
Spectrum
Three Dimensional
Topological Analysis
User Involvement
Visualization Technique
Volume Rendering
Volume Visualization
Transfer Function
Subscribe
Academic
Publications
The Topological Effects of Smoothing
The Topological Effects of Smoothing,10.1109/TVCG.2011.74,IEEE Transactions on Visualization and Computer Graphics,Sohail Shafii,Scott E. Dillard,Mari
Edit
The Topological Effects of Smoothing
BibTex

RIS

RefWorks
Download
Sohail Shafii
,
Scott E. Dillard
,
Mario Hlawitschka
,
Bernd Hamann
OPOLOGICAL analysis is an increasingly important approach for visualization and analysis of
scientific data
in many fields, with relevance for data sets originating in a broad
spectrum
of applications, ranging from
materials science
to medicine.
Transfer function
design for
volume rendering
can be viewed as an application of topological characterization, where certain regions of data sets corresponding to ranges of function values are assigned
optical properties
such as color and opacity. These regions allow a usertoeasilyidentifyanddelineatesignificantstructuresina data set.
Transfer function
methods based on simple thresholding remain attractive due to their simplicity, reproducibility, and minimal user involvement, but they cannot be usedwhensignificantnoiseispresentinthedata.Inaddition, noise generally leads to isosurfaces that contain many spurious surface components, which complicates queries involving the number, size, and distribution of different regions. When having to process and visualize noisy data, smoothingisalwaysanalluringoption,leadingtoisosurfaces withfewercomponentsandsmootherboundaries.However, smoothing has the potential to drastically alter the data to the point where one draws invalid conclusions. We present a twostage method to track and visualize the topological changes that occur when smoothing a scalarvalued data set defined over a volumetric, threedimensional (3D) domain. During the tracking stage, we apply smoothing up to a point where a meaningful interpretation of the data is no longer possible. We track the topological changes that occur, specifically the creation and destruction of extremal points that merge with other topological features that persist. In the visualization stage that follows, the user can select the topological events that affect the original
noisy data
set by applying labels (or colors) to different portions of the data. To summarize, we have developed a general
topological analysis
method that requires little input from the user. We first provide an introduction to
Morse theory
and contour trees in Section 2. We describe the methods used in Section 3 and discuss the results obtained with our methods in Section 4. Future research possibilities are covered in Section 5.
Journal:
IEEE Transactions on Visualization and Computer Graphics  TVCG
, vol. 18, no. 1, pp. 160172, 2012
DOI:
10.1109/TVCG.2011.74
Cumulative
Annual
View Publication
The following links allow you to view full publications. These links are maintained by other sources not affiliated with Microsoft Academic Search.
(
ieeexplore.ieee.org
)
(
ieeexplore.ieee.org
)
References
(41)
Noise Theory
(
Citations: 995
)
R. A. King
Journal:
Nature
, vol. 183, no. 4658, pp. 353353, 1959
Hybrid techniques for realtime radar simulation
(
Citations: 29
)
Roger L. Boyell
,
Henry Ruston
Conference:
Fall Joint Computer Conference
, pp. 445458, 1963
Computing contour trees in all dimensions
(
Citations: 163
)
Hamish Carr
,
Jack Snoeyink
,
Ulrike Axen
Conference:
ACMSIAM Symposium on Discrete Algorithms  SODA
, pp. 918926, 2000
Simple and optimal outputsensitive construction of contour trees using monotone paths
(
Citations: 28
)
Yijen Chiang
,
Tobias Lenz
,
Xiang Lu
,
Günter Rote
Journal:
Computational Geometry: Theory and Applications  COMGEO
, vol. 30, no. 2, pp. 165195, 2005
Parallel Computation of the Topology of Level Sets
(
Citations: 25
)
Valerio Pascucci
,
Kree Colemclaughlin
Journal:
Algorithmica
, vol. 38, no. 1, pp. 249268, 2003