Layered Reconstruction for Defocus and Motion Blur

Jacob Munkberg, Karthik Vaidyanathan, Jon Hasselgren, Petrik Clarberg, Tomas Akenine-Möller

Research output: Contribution to journalArticlepeer-review

Abstract

Light field reconstruction algorithms can substantially decrease the noise in stochastically rendered images. Recent algorithms for defocus blur alone are both fast and accurate. However, motion blur is a considerably more complex type of camera effect, and as a consequence, current algorithms are either slow or too imprecise to use in high quality rendering. We extend previous work on real-time light field reconstruction for defocus blur to handle the case of simultaneous defocus and motion blur. By carefully introducing a few approximations, we derive a very efficient sheared reconstruction filter, which produces high quality images even for a low number of input samples. Our algorithm is temporally robust, and is about two orders of magnitude faster than previous work, making it suitable for both real-time rendering and as a post-processing pass for offline rendering.
Original languageEnglish
Pages (from-to)81-92
JournalComputer Graphics Forum
Volume33
Issue number4
DOIs
Publication statusPublished - 2014

Subject classification (UKÄ)

  • Computer Science

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