Geometric Image Registration under Locally Variant Illuminations Using Huber M-estimator

  • M. M. Fouad
  • R. M. Dansereau
  • A. D. Whitehead
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6134)


In this paper, we extend our previous work on presenting a registration model for images having arbitrarily-shaped locally variant illuminations from shadows to multiple shading levels. These variations tend to degrade the performance of geometric registration and impact subsequent processing. Often, traditional registration models use a least-squares estimator that is sensitive to outliers. Instead, we propose using a robust Huber M-estimator to increase the geometric registration accuracy (GRA). We demonstrate the proposed model and compare it to other models on simulated and real data. This modification shows clear improvements in terms of GRA and illumination correction.


Image Registration Variant Illumination Global Illumination Registration Model Illumination Correction 
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 2010

Authors and Affiliations

  • M. M. Fouad
    • 1
  • R. M. Dansereau
    • 1
  • A. D. Whitehead
    • 1
  1. 1.Dept. of Systems and Computer EngineeringCarleton UniversityOttawaCanada

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