GA–SSD–ARC–NLM for Parametric Image Registration

  • Felix Calderon
  • Leonardo Romero
  • Juan Flores
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4225)


We present the GA–SSD–ARC–NLM, a new robust parametric image registration technique based on the non–parametric image registration SSD–ARC algorithm. This new algorithm minimizes a new cost function quite different to the original non-parametric SSD-ARC, which explicitly models outlier punishments, using a combination of a genetic algorithm and the Newton–Levenberg–Marquardt method. The performance of the new method was compared against two robust registration techniques: the Lorentzian Estimator and the RANSAC method. Experimental tests using gray level images with outliers (noise) were done using the three algorithms. The goal was to find an affine transformation to match two images; the new method improves the other methods when noisy images are used.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Felix Calderon
    • 1
  • Leonardo Romero
    • 1
  • Juan Flores
    • 1
  1. 1.División de Estudios de Posgrado. Facultad de Ingeniería EléctricaUniversidad Michoacana de San Nicolás de HidalgoMorelia, MichoacánMéxico

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