Color Image Restoration Based on Dynamic Recurrent RBF Neural Network
Hongwei Ge, Weinan Yang · 2007
A kind of nearest neighbor classification (NNC) based on dynamic recurrent RBF neural network is used to restore color image. It combines a MLP and a RBF neural network, and allows for explicit representation of prototype patterns as network parameters. The system structure is self-adaptive, and the prototypes can be added or removed freely. The dynamic classification implemented by the network eliminates all comparisons, which are the vital steps of the conventional NNC process. Some results of image de-noising show the high performance of this model. Moreover, the new model also provides excellent robustness with respect to various percentages of noise in our testing examples.