A Hardware-Assisted Hybrid Rendering Technique for Interactive Volume Visualization

Brett Wilson

Kwan-Liu MaUniversity of California, Davis

Patrick S. McCormickLos Alamos National Laboratory

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Overview

Problems with large-scale volume visualization Hybrid rendering

– Hybrid data generation– Storage– Rendering

Results Future work

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Large-scale volume visualization

Data: Resolutions are 5123 (128MB) and higher

Commodity PC: 1GB RAM, 128MB video memory

Want to display large data on these small computers

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Combine volume and point rendering

Large, slowly varying regions– Hardware volume rendering

Small areas of high detail– Point-based rendering

Combine the efficiency of both rendering techniques

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Selected previous work

Hardware volume rendering [Cabral 1994] [Wilson 1994]– Multi-resolution [LaMar 1999] [Weiler 2000]– Parallel [Kniss 2001] [Lum 2001] [Lum 2002]

Splatting [Westover 1989]– Extensions [Mao 1996] [Mueller 1999]– EWA Volume Splatting [Zwicker 2001][Ren 2002]

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Generating hybrid data

Low-resolutionvolume

Originalvolume

Generatedpoints

Region ofhigh error

Generating low-resolutionvolume data

Generating points forregions of high error

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Point selection

Error evaluated on a regular grid– Usually same resolution as original data

Points generated where error is above a given threshold– Also allows goal-oriented generation

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Hybrid data generation overview

Original data

Low-res volume data Point data

(interpolation)

(difference &threshold)

Result data

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Rendering opaque features

Original vol. HybridLow-res vol. Point data

+ =

• Points enhance boundary of opaque feature

• Transparent area can’t be made more transparent

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Rendering transparent features

Original vol. HybridLow-res vol. Point data

+ =

• Points enhance boundary of opaque surroundings

• Transparent feature can’t be made more transparent

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Dealing with overestimation errors

Most important features usually drawn as opaque– Effect minimized

Pick a low-resolution volume that is always more transparent than the original– Limits transfer functions– Requires a lot of points

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Rendering volumetric data

Texture-mapped polygonsrendered back-to-front

Eye

Result is the illusion of volume

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Computing volume appearance

Color/opacity– Paletted texture lookup for

transfer function value

Lighting– Paletted texture lookup for

specular/diffuse

Register combiners

Result

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Rendering hybrid data

Slices of pointsare interleavedwith polygons

Eye

Each slice of pointsis loaded into a display list.

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Computing point appearance

Color/opacity– Paletted texture lookup for

transfer function value

Lighting– Paletted texture lookup for

specular/diffuse

Scale by error value– Map into transfer-function

space with 2D texture lookup

Register combiners

Result

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Hybrid data storage

Volumetric data– 1 byte value– 1 byte normal

Point data– 3 to 6 byte position (depending on grid resolution)– 1 byte original value– 1 byte normal – 1 byte error

Space: 5123 = 2563 + 26 M points

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Results

Simulation– Argon bubble simulation, [Lawrence Berkeley National Lab]

Medical– MRI of a human chest, [Kubota Co., Japan]

Mechanical– Furby® (mechanical toy) CT scan, [Los Alamos/Hytec]

Test machine:– 1GHz Pentium III Xeon, 1GB RAM, 128MB GeForce 4 Ti 4600

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Results: 5123 Argon bubble simulation

Area of focusFull frame(one of a time-varying simulation)

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Results: 5123 Argon bubble simulation

Original:5123 268MB

Low-res volume:2563

33MB

Hybrid:2563 + 361K points37MB(1/64 error threshold)

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Results: 5123 Chest MRI

211283+11M

Hybrid 1283 + 4M points1/12 error threshold, 5123 grid40MB0.29 s/frame

1283 volume4MB0.01 s/frame

5123 volume268MB0.35 s/frame

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Hybrid 2563 + 7M points1/64 error threshold, 5123 grid97MB0.47 s/frame

2563 volume33MB0.04 s/frame

5123 volume268MB0.35 s/frame

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Results: 512 512 2048 Furby®

Mechanical data– Many sharp edges– Very high dynamic range– Very high resolution

Full size = 1 GB (including normals)

Non-square voxels

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Results: 512 512 2048 Furby®

2563 33MB0.07 s/frame

2563 + 3M points (5123, 1/16 error)

59MB0.36 s/frame

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Results: 512 512 2048 Furby®

2563 + 3M points (5123, 1/16 error)

59MB0.36 s/frame

2563 + 4.7M points (10243, 1/8 error)

71MB0.58 s/frame

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Future enhancements

Non-cubic error sampling interval– View dependent

Automatic parameter selection

Optimize point size/opacity

Incremental point loading and rendering

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Conclusions

New way to reduce data size for previewing– Preserves fine details

Allows very large data to be viewed on small computers– Acceptable performance

Effective for simulation, medical, and mechanical data

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Acknowledgements

Los Alamos National Laboratory DOE SciDAC NSF contract ACI 9983641 (PECASE Award) LSSDSV contract ACI 9982251

Data– Argon bubble: Center for Computational Sciences and

Engineering at the Lawrence Berkeley National Laboratory

– Chest MRI: Dr. H. Miyachi at Kubota Co., Japan

– Furby®: Anthony Davis at Hytec Inc. and

Bill Ward of the Los Alamos National Laboratory