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Single Image Restoration of Outdoor Scenes

  • Codruta Orniana Ancuti
  • Cosmin Ancuti
  • Philippe Bekaert
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6855)

Abstract

We present a novel strategy to restore outdoor images degraded by the atmospheric phenomena such as haze or fog. Since both the depth map of the scene and the airlight constant are unknown, this problem is mathematically ill-posed. Firstly, we present a straightforward approach that is able to estimate accurately the airlight constant by searching the regions with the highest intensity. Afterwards, based on a graphical Markov random field (MRF) model, we introduce a robust optimization framework that is able to transport the local minima over large neighborhoods while smoothing the transmission map but also preserving the important depth discontinuities of the estimated depth. The method has been tested extensively for real outdoor images degraded by haze or fog. The comparative results with the existing state-of-the-art techniques demonstrate the advantage of our approach.

Keywords

Markov Random Field Outdoor Scene Depth Discontinuity Unsharp Mask Restoration Result 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Codruta Orniana Ancuti
    • 1
  • Cosmin Ancuti
    • 1
  • Philippe Bekaert
    • 1
  1. 1.Expertise Center for Digital MediaHasselt University - tUL -IBBTDiepenbeekBelgium

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