Image representation by self-organizing conformal network
Conformal mappings are incorporated into the self-organization model to represent images harmonically. This network is used to partition an image into quadrilateral regions, where each region contains similar features. We then map each region to a corresponding square region to unify information representation and facilitate computations, This mapping is constructed to presence spatial information while complying with the conformal property of the network. An approximated image in each square region provides us with an effective representation of the image in both modeling and compression applications. This approach has been particularly developed for large continues images.
conformal mapping neural network image modeling self-organizing network image compression