Adaptive image interpolation using probabilistic neural network

Sheng Hsien Hsieh, Ching Han Chen

Research output: Contribution to journalArticlepeer-review

15 Scopus citations


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 languageEnglish
Pages (from-to)6025-6029
Number of pages5
JournalExpert Systems with Applications
Issue number3 PART 2
StatePublished - Apr 2009


  • Interpolation
  • Particle swarm optimization
  • Probabilistic neural networks
  • Single neuron


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