A kalman-filtering approach to high dynamic range imaging for measurement applications

Eric Dedrick, Daniel Lau

Research output: Contribution to journalArticlepeer-review

10 Scopus citations


High dynamic range imaging (HDRI) methods in computational photography address situations where the dynamic range of a scene exceeds what can be captured by an image sensor in a single exposure. HDRI techniques have also been used to construct radiance maps in measurement applications; unfortunately, the design and evaluation of HDRI algorithms for use in these applications have received little attention. In this paper, we develop a novel HDRI technique based on pixel-by-pixel Kalman filtering and evaluate its performance using objective metrics that this paper also introduces. In the presented experiments, this new technique achieves as much as 9.4-dB improvement in signal-to-noise ratio and can achieve as much as a 29% improvement in radiometric accuracy over a classic method.

Original languageEnglish
Article number5981389
Pages (from-to)527-536
Number of pages10
JournalIEEE Transactions on Image Processing
Issue number2
StatePublished - Feb 2012


  • High dynamic range imaging (HDRI)

ASJC Scopus subject areas

  • Software
  • Computer Graphics and Computer-Aided Design


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