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A Dual Theory of Inverse and Forward Light Transport

  • Jiamin Bai
  • Manmohan Chandraker
  • Tian-Tsong Ng
  • Ravi Ramamoorthi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6312)

Abstract

Inverse light transport seeks to undo global illumination effects, such as interreflections, that pervade images of most scenes. This paper presents the theoretical and computational foundations for inverse light transport as a dual of forward rendering. Mathematically, this duality is established through the existence of underlying Neumann series expansions. Physically, we show that each term of our inverse series cancels an interreflection bounce, just as the forward series adds them. While the convergence properties of the forward series are well-known, we show that the oscillatory convergence of the inverse series leads to more interesting conditions on material reflectance. Conceptually, the inverse problem requires the inversion of a large transport matrix, which is impractical for realistic resolutions. A natural consequence of our theoretical framework is a suite of fast computational algorithms for light transport inversion – analogous to finite element radiosity, Monte Carlo and wavelet-based methods in forward rendering – that rely at most on matrix-vector multiplications. We demonstrate two practical applications, namely, separation of individual bounces of the light transport and fast projector radiometric compensation to display images free of global illumination artifacts in real-world environments.

Keywords

Dual Theory Global Illumination Light Transport High Dynamic Range Image Indirect Illumination 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Supplementary material

978-3-642-15552-9_22_MOESM1_ESM.pdf (7.3 mb)
Electronic Supplementary Material (7,521 KB)

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Jiamin Bai
    • 1
  • Manmohan Chandraker
    • 1
  • Tian-Tsong Ng
    • 2
  • Ravi Ramamoorthi
    • 1
  1. 1.University of CaliforniaBerkeley
  2. 2.Institute for Infocomm ResearchSingapore

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