An investigation into cellular neural networks internal dynamics applied to image processing

Abstract

Interesting perspectives in image processing with cellular neural networks can be emphasized from an investigation into the internal states dynamics of the model. Most of the cellular neural networks design methods intend to control internal states dynamics in order to get a straight processing result. The present one involves some kind of internal states preprocessing so as to finally achieve processing otherwise unrealizable. Applications of this principle to the building of complex processing schemes, gray level preserving segmentation and selective brightness variation are presented.