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Interactive Rendering of Large Volume DataSets (IEEE Viz 2002)

Interactive Rendering of Large Volume DataSets (IEEE Viz 2002). Stefan Guthe,WSI/GRIS, University of Tubingen. Summary. Data is stored using multires octree Wavelet compression – wavelet coefficients are further compressed

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Interactive Rendering of Large Volume DataSets (IEEE Viz 2002)

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  1. Interactive Rendering of Large Volume DataSets (IEEE Viz 2002) Stefan Guthe,WSI/GRIS, University of Tubingen

  2. Summary • Data is stored using multires octree • Wavelet compression – wavelet coefficients are further compressed • At render time, the data is decompressed on the fly and rendered using 3D texture hardware • Rendering is done according to view dependent priority • Good frame rates – but final image size is low (256 * 256)

  3. Wavelet compression • The compression involves 2 steps – wavelet representation of data and huffman, run-length or arithmetic encoding to further reduce space for wavelet coefficients • Compression ratio of huffman encoding (used in the implementation) is 3:4:1 for lossless compression

  4. Projective classification and rendering • A projective classification eliminates rendering voxels not in the view frustum • View dependent priority is assigned to nodes depending on their voxel depths • The number of voxels that can be displayed is preset (depending on texture memory) • A priority queue is used to insert node by node of the octree, the closer voxel nodes having higher priority

  5. Rendering with priority • The node with higher priority in the queue is fetched • Its high frequency wavelet coefficients are decompressed and the child is inserted in the queue • This process halts when the number of voxels exceed the preset limit

  6. Trilinear interpolation and block size effects • The volume is decomposed hierarchically into k3 (usually k=16) blocks, which are rendered as 3D textures using hardware • Block size must be a power of 2, because of OpenGL texture restrictions • The target image is 256*256 pixels For all 256*256 possible values of entry and exit, volume integrals are pre-computed • Tri-linear interpolation done by texture hardware might need multiple blocks in the octree – therefore neighboring blocks in the octree might have to be coalesced • A greater block size (k = 32) reduces this overhead

  7. Caching • Caching of decompressed data is required for interactive frame rates. Unaddressed issues: Interpolating between multiple resolutions,

  8. Results • Visible human dataset • 2048 X 1216 X 1877 X 12 bit (~6.4 G) • Final image size rendered is 256 X 256 • Frame rate vs compression ration vs PSNR

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