Abstract:

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