A Bio-inspired Computer Fovea Model based on Hexagonal-type Cellular Neural Networks

In this work we propose a novel computer fovea model based on hexagonal-type cellular neural networks (hCNN). The hCNN represents a new image processing architecture that is motivated by the overwhelming evidence for hexagonal image processing in biological systems. The necessary new coupling templates and basic hCNN image operators are introduced. The fovea model includes the biological mechanisms of the photoreceptors, the horizontal cells, the ganglions, the bipolar cells, and their cooperation. Thus the model describes the signal processing from the optical stimulation at retina to the output of the ganglion cells. Different building blocks of the model turned out to be useful for practical image enhancement algorithms. Two such applications are considered in this work, namely the image sharpness improvement and the color constancy algorithm.