This paper proposes an image interpolation model based on probabilistic neural network (PNN). The method adjusts automatically the smoothing parameters for varied smooth/edge image region, and takes into consideration both smoothness (flat region) and sharpness (edge region) characteristics at the same model. A single neuron, combined with PSO training, is used for sharpness/smoothness adaptation. Finally, we report the performance of these newly proposed methods in other image interpolation method.
|Number of pages||5|
|Journal||Expert Systems with Applications|
|Issue number||3 PART 2|
|State||Published - Apr 2009|
- Particle swarm optimization
- Probabilistic neural networks
- Single neuron