Journal of Jishou University(Natural Sciences Edition)

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Regional Image Interpolation Algorithms with Back-Propagation Artificial Neural Network

QIAN Yurong,YU Jiong,YING Changtian,YANG Xingyao   

  1. (School of Software,Xinjiang University,Urumqi 830008,China)
  • Online:2016-05-25 Published:2016-06-24


In order to improve the quality of image interpolation,back-propagation artificial neural network (BP-ANN) with self-learning,adaptive and generalization ability has been used to carry out the regional image interpolation research.Missing pixel in image is divided into smooth region and edge region,each region corresponding to a BP-ANN interpolation operation.To identify the topology structure,sampling mode and the interpolation process of regional BP-ANN,three experiments were performed.The experimental results show that best balance between CPU-time consumption and visual quality lies in 8-16-1 topology of BP-ANN;compared with the classical LA interpolation algorithm,our proposed algorithm provides 0.593 8 dB higher PSNR while performed better visual quality.

Key words: interpolation, back propagation artificial neural network, linear average interpolation, peak signal to noise radio, network topology

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