Iterative Tuning of Simple Cells for Contrast Invariant Edge Enhancement

  • Authors:
  • Marina Kolesnik;Alexander Barlit;Evgeny Zubkov

  • Affiliations:
  • -;-;-

  • Venue:
  • BMCV '02 Proceedings of the Second International Workshop on Biologically Motivated Computer Vision
  • Year:
  • 2002

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Abstract

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.