Iterative Tuning of Simple Cells for Contrast Invariant Edge Enhancement

  • Marina Kolesnik
  • Alexander Barlit
  • Evgeny Zubkov
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2525)


This work describes a novel model for orientation tuning of simple cells in V1. The model has been inspired by a regular structure of simple cells in the visual primary cortex of mammals. Two new features distinguish the model: the iterative processing of visual inputs; and amplification of tuned responses of spatially close simple cells. Results show that after several iterations the processing converges to a stable solution while making edge enhancement largely contrast independent. The model suppresses weak edges in the vicinity of contrastive luminance changes but enhances isolated low-intensity changes. We demonstrate the capabilities of the model by processing synthetic as well as natural images.


Ganglion Cell Visual Input Lateral Geniculate Nucleus Simple Cell Perceptual Grouping 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Marina Kolesnik
  • Alexander Barlit
    • 1
  • Evgeny Zubkov
    • 1
  1. 1.Fraunhofer Institute for Media CommunicationSankt-AugustinGermany

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