Combining observation models in dual exposure problems using the Kullback-Leibler divergence

M. Tallón*, J. Mateos, S. D. Babacan, R. Molina, Aggelos K Katsaggelos

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

Photographs acquired under low-lighting conditions require long exposure times and therefore exhibit significant blurring due to the shaking of the camera. Using shorter exposure times results in sharper images but with a very high level of noise. By taking a pair of blurred/noisy images it is possible to reconstruct a sharp image without noise. This paper is devoted to the combination of observation models in the blurred/noisy image pair reconstruction problem. By examining the difference between the blurred image and the blurred version of the noisy image a third observation model is obtained. Based on the minimization of a linear convex combination of Kullback-Leibler divergences between posterior distributions, a procedure to combine the three observation models is proposed in the paper. The estimated images are compared with images provided by other reconstruction methods.

Original languageEnglish (US)
Pages (from-to)323-327
Number of pages5
JournalEuropean Signal Processing Conference
StatePublished - Dec 1 2010
Event18th European Signal Processing Conference, EUSIPCO 2010 - Aalborg, Denmark
Duration: Aug 23 2010Aug 27 2010

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering

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