Abstract
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.
Original language | English |
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Pages (from-to) | 6025-6029 |
Number of pages | 5 |
Journal | Expert Systems with Applications |
Volume | 36 |
Issue number | 3 PART 2 |
DOIs | |
State | Published - Apr 2009 |
Keywords
- Interpolation
- Particle swarm optimization
- Probabilistic neural networks
- Single neuron