Image inpainting based on BP neural network
HE Wen-x · Journal of Jiangxi University of Science and Technology · 2014
BP neural network used to repair digital images has be proposed,considering the traits of BP neural network which has an extraordinary capacity for learning and the non-linear mapping.Because ordinary BP neural network converge at a slower rate,fall in to a local minimum easily,and produce oscillatory behavior,introduction of momentum on the basis of the gradient descent algorithm is considered.It get faster convergence speed,smaller oscillation phenomena.Similar blocks will be found in accordance with the border of areas to be restored.With similar block pixel data,BP neural network get its weights and thresholds.The experiment results show this model spend less time than the model utilized partial differential equation(PDE)(for example BSCB),and this model has larger ISNR than PDE model.