Abstract
In order to solve the phenomena that harsh coal mine environment will lead to coal mine monitoring image degradation, a K-fold Cross-Validation image restoration algorithm BP neural network was proposed. Firstly, the images will be blurred by Gaussian white noise. Then, the blurred image and original image match pairs. When the training error and validation error is equal, stop the network training, select the training error and test error are smaller as the optimal model. Finally, bring the blurred image to the restoration model and image processing. Experiment shows that the K-Fold Cross-Validation BP neural network model for image restoration of generalization performance and fitting precision both meet the requirements. Keywords-Image restorations;K-fold Cross-Validation;BP neural network; Coal mine.
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