GPU accelerated image aligned splatting

  • Authors:
  • Neophytos Neophytou;Klaus Mueller

  • Affiliations:
  • Center for Visual Computing, Computer Science, Stony Brook University;Center for Visual Computing, Computer Science, Stony Brook University

  • Venue:
  • VG'05 Proceedings of the Fourth Eurographics / IEEE VGTC conference on Volume Graphics
  • Year:
  • 2005

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Abstract

Splatting is a popular technique for volume rendering, where voxels are represented by Gaussian kernels, whose pre-integrated footprints are accumulated to form the image. Splatting has been mainly used to render pre-shaded volumes, which can result in significant blurring in zoomed views. This can be avoided in the image-aligned splatting scheme, where one accumulates kernel slices into equi-distant, parallel sheet buffers, followed by classification, shading, and compositing. In this work we attempt to evolve this algorithm to the next level: GPU based acceleration. First we describe the challenges that the highly parallel "Gather" architecture of modern GPUs poses to the "Scatter" based nature of a splatting algorithm. We then describe a number of strategies that exploit newly introduced features of the latest-generation hardware to address these limitations. Two crucial operations to boost the performance in image-aligned splatting are the early elimination of hidden splats and the skipping of empty buffer-space. We will describe mechanisms which take advantage of the early z-culling hardware facilities to accomplish both of these operations efficiently in hardware.