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Streaming multigrid for gradient-domain operations on large images

Published: 01 August 2008 Publication History

Abstract

We introduce a new tool to solve the large linear systems arising from gradient-domain image processing. Specifically, we develop a streaming multigrid solver, which needs just two sequential passes over out-of-core data. This fast solution is enabled by a combination of three techniques: (1) use of second-order finite elements (rather than traditional finite differences) to reach sufficient accuracy in a single V-cycle, (2) temporally blocked relaxation, and (3) multi-level streaming to pipeline the restriction and prolongation phases into single streaming passes. A key contribution is the extension of the B-spline finite-element method to be compatible with the forward-difference gradient representation commonly used with images. Our streaming solver is also efficient for in-memory images, due to its fast convergence and excellent cache behavior. Remarkably, it can outperform spatially adaptive solvers that exploit application-specific knowledge. We demonstrate seamless stitching and tone-mapping of gigapixel images in about an hour on a notebook PC.

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Information

Published In

cover image ACM Transactions on Graphics
ACM Transactions on Graphics  Volume 27, Issue 3
August 2008
844 pages
ISSN:0730-0301
EISSN:1557-7368
DOI:10.1145/1360612
Issue’s Table of Contents

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 August 2008
Published in TOG Volume 27, Issue 3

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Author Tags

  1. B-spline finite elements
  2. Poisson equation
  3. gigapixel images
  4. multi-level streaming
  5. out-of-core multigrid solver

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