Simple cell interaction for iterative contrast detection

This work describes a novel model for contrast detection inspired by regular spatial structure of simple cells in the visual cortex of mammals. The model employs major cortical connections in the laminar circuitry of extrastriate visual pathways and the area V1 of the visual cortex. The model employs two new features, namely, the iterative processing of visual inputs and amplification of tuned responses of spatially close simple cells in V1. Results show that after several iterations the processing converges to a stable solution while making edge detection being largely contrast independent. The model suppresses spurious noise in the vicinity of contrastive luminance changes while enhancing isolated low-intensity changes. We demonstrate the capabilities of the model by processing synthetic as well as natural images and compare our results to Canny edge detector.