A Local-Information-Based Blind Image Restoration Algorithm Using a MLP

Based on a multilayer perceptron (MLP), a blind image restoration method is presented. The algorithm considers both local region information and edge information of an image. To reduce the dimension of the network's input, a sliding window approach is employed to extract the features of the blurred image, which makes use of local region information. For the purpose of accelerating training and improving the restoration performance, the edge part and the smooth part in an image are separated and then used as training sets, respectively. A mapping model between the blurred image and the clear one is established through training the MLP with LM algorithm and then it is utilized to restore the blurred image. The simulation results demonstrate the proposed method feasible for image restoration.

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