Display of Surfaces from Volume Data
IEEE Computer Graphics and Applications
Efficient ray tracing of volume data
ACM Transactions on Graphics (TOG)
Three-pass affine transforms for volume rendering
VVS '90 Proceedings of the 1990 workshop on Volume visualization
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Introduction to parallel algorithms and architectures: array, trees, hypercubes
Fast volume rendering using a shear-warp factorization of the viewing transformation
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
2D and 3D optimal parallel image warping
Journal of Parallel and Distributed Computing
Real-time volume rendering on shared memory multiprocessors using the shear-warp factorization
PRS '95 Proceedings of the IEEE symposium on Parallel rendering
Parallel stereocorrelation on a reconfigurable multi-ring network
The Journal of Supercomputing - Special issue on parallel and distributed processing
Three-dimensional rotations by three shears
Graphical Models and Image Processing
Time and space optimal data parallel volume rendering using permutation warping
Journal of Parallel and Distributed Computing
Illumination for computer generated pictures
Communications of the ACM
3d Computer Graphics
Understanding Parallel Supercomputing
Understanding Parallel Supercomputing
Analysis of a Parallel Volume Rendering System Based on the Shear-Warp Factorization
IEEE Transactions on Visualization and Computer Graphics
Parallel Volume Rendering Using Binary-Swap Compositing
IEEE Computer Graphics and Applications
Distributed stereo-correlation algorithm
Computer Communications
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Projections are widely used in machine vision, volume rendering, and computer graphics. For applications with 3D volume data, we design a parallel projection algorithm on SIMD mesh-connected computers and implement the algorithm on the Parallel Algebraic Logic (PAL) computer. The algorithm is a parallel ray casting algorithm for both orthographic and perspective projections. It decomposes a volume projection into two transformations that can be implemented in the SIMD fashion to solve the data distribution and redistribution problem caused by non-regular data access patterns in volume projections.