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.
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Kolesnik, M., Barlit, A., Zubkov, E. (2002). Iterative Tuning of Simple Cells for Contrast Invariant Edge Enhancement. In: Bülthoff, H.H., Wallraven, C., Lee, SW., Poggio, T.A. (eds) Biologically Motivated Computer Vision. BMCV 2002. Lecture Notes in Computer Science, vol 2525. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36181-2_3
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DOI: https://doi.org/10.1007/3-540-36181-2_3
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