Compression Domain Volume Processing
I. Compression Domain
Volume Rendering: Voxel-Based
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Description:
Volumetric data sets require enormous storage capacity even at moderate
resolution levels. The excessive storage demands not only stress the capacity
of the underlying storage and communications systems, but also seriously
limit the speed of volume rendering due to data movement and manipulation.
A novel volumetric data visualization scheme is proposed and implemented
in this work that renders 2D images directly from compressed 3D data sets.
The novelty of this algorithm is that rendering is performed on the compressed
representation of the volumetric data without pre-decompression.
As a result, the overheads associated with both data movement and rendering
are significantly reduced. The proposed algorithm generalizes previously
proposed whole-volume frequency-domain rendering schemes by first dividing
the 3D data set into subcubes, transforming each subcube to a frequency-domain
representation, and applying the Fourier Projection Theorem to produce
the projected 2D images according to given viewing angles. Compared to
the whole-volume approach, the subcube-based scheme not only achieves higher
compression efficiency by exploiting local coherency, but also improves
the quality of resultant rendering images because it approximates the occlusion
effect on a subcube by subcube basis.
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Publications:
Tzi-cker Chiueh, Chuan-kai Yang, Taosong He, Hanspeter Pfister, Arie
Kaufman, "Integrated
Volume Compression and Visualization," in IEEE Visualization '97, Phoenix,
AZ, October 1997.
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II. Survey on Integration
of Volume Compression and Visualization
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Description:
Volume visualization has become more and more important in modern world
due to its wide applicability. Numerous techniques have been developed
to render data sets in the form of regular grids (voxel data) and irregular
grids. As the volume data sets grow bigger and bigger, data compression
algorithms are required to reduce the disk storage size, and potentially
the memory size during rendering as well. This paper surveys several techniques
of volume visualization and volume compression, together with their integration
or interaction. In general the strategies include: decompression the whole
data set before rendering, on-the-fly rendering during decompression, on-the-fly
decompression during rendering, and rendering in the compression domain.
Furthermore, since quantization is almost inevitable for efficient lossy
data compression, we also reported experiment results that show the impact
on the quality of the final rendered images of quantization of data sets
in the 3D spatial and transformed domains.
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Publications:
Chuan-kai Yang, "Integration
of Volume Compression and Visualization: A Survey," Research Proficiency
Exam Report, September 2000.
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III. Compression
Domain Volume Rendering: Tetrahedron-Based
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Description:
Very large irregular-grid data sets are represented as tetrahedral
meshes and may incur significant disk I/O access overhead in the rendering
process. An effective way to alleviate the disk I/O overhead associated
with rendering large tetrahedral mesh is to reduce the I/O bandwidth requirement
through compression. Existing tetrahedral mesh compression algorithms focus
only on compression efficiency and cannot be readily integrated into the
mesh rendering process, and thus demand that a compressed tetrahedral mesh
be decompressed before it can be rendered into a 2D image. This paper presents
an integrated tetrahedral mesh compression and rendering algorithm called
Gatun, which allows compressed tetrahedral meshes to be rendered incrementally
as they are being decompressed, thus leading to an efficient irregular
grid rendering pipeline. Both compression and rendering algorithms in Gatun
exploit the same local connectivity information among adjacent tetrahedra,
and thus can be tightly integrated into a unified implementation framework.
Our tetrahedral compression algorithm is specifically designed to facilitate
the integration with irregular grid renderer without any compromise in
compression efficiency. A unique performance advantage of Gatun is its
ability to reduce the run-time memory footprint requirement by releasing
memory allocated to tetrahedra as early as possible. As a result, Gatun
is able to decrease rendering time by one or two orders of magnitude for
very large tetrahedral mesh whose size exceeds the amount of physical memory.
At the same time, the smaller working set and better access locality of
Gatun improve the rendering performance by up to 30%, even when the input
tetrahedral mesh is entirely memory-resident.
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Publications:
Chuan-kai Yang, Tulika Mitra, Tzi-cker Chiueh, "On-the-Fly
Rendering of Losslessly Compressed Irregular Volume Data," in IEEE
Visualization '2000, Salt Lake City, Utah, October 2000.
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IV. Compression
Domain Volume Rendering & Simplification: Tetrahedron-Based
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Description
Very large irregular-grid volume data sets are typically represented
as tetrahedral mesh and require substantial disk I/O and rendering computation.
One effective way to reduce this stringent resource demand is compression.
Previous research showed how rendering and decompression of a losslessly
compressed rregular-grid data set can be integrated into a one-pass computation.
This work takes it one step further by showing that a losslessly compressed
irregular volume data set can be simplified while it is being decompressed
and that simplification, decompression, and rendering can be again integratedinto
a pipeline that requires only a single pass through the data sets. Since
simplification is a form of lossy compression, the on-the-fly volume simplification
algorithm provides a powerful echanism to dynamically create versions of
a tetrahedral mesh at multiple resolution levels directly from its losslessly
compressed representation, which also orresponds to the finest resolution
level. In particular, an irregular-grid volume renderer can exploit this
mechanism to adjust the amount of rendering computation to match a given
hardware/software platform while maintaining adequate interactivity. The
proposed tetrahedral mesh simplification algorithm and its integration
with volume decompression and rendering has been successfully implemented
in the Gatun system. Performance measurements on the Gatun prototype show
that simplification only adds less than 5% of performance overhead but
can improve the rendering performance by a factor up to 2 without noticeable
rendering quality degradation. Together with a "multi-resolution presimplification"
scheme, Gatun can perform the so called "time-critical rendering" by adjusting
the simplification ratio to achieve the desired rendering frame rate.
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Publications:
Chuan-kai Yang, Tzi-cker Chiueh, "An
Integrated Pipeline of Decompression, Simplification and Rendering for
Irregular Volume Data," submitted for publications.
Chuan-kai Yang, Tzi-cker Chiueh, "On-the-Fly
Processing of Compressed Volume Data," Phd Dissertation, August, 2002.
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V. Compression
Domain Out-of-Core Iso-Surface Extraction
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Description
To demonstrate how volume compression can also be integrated into other
applications as well, we have also developed an algorithm that combines
volume compression with iso-surface extraction into a one-pass algorithm.
Instead of a ``coordinate-based'' decomposition used by conventional out-of-core
iso-surface extraction algorithms, we choose to use a``layer-based''
structure. Each such layer contains a collection of tetrahedral whose associated
scalar values fall within a specific range, and is compressed independently
to reduce the storage requirement. The layer structure is particularly
suitable for
out-of-core iso-surface extraction as one can perform on-the-fly iso-surface
extraction during decompression, and the computation only involves the
layer
that contains the query value, rather than the entire data set.
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Publications:
Chuan-kai Yang, Tzi-cker Chiueh, "On-the-Fly
Processing of Compressed Volume Data," Phd Dissertation, August, 2002.
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