A Method for Restoring Motion-Blurred License Plate Images Based on Generative Adversarial Network
To solve the problem of license plate recognition algorithms failing due to blurriness caused by fast-moving vehicles,this paper studies the Generative Adversarial Network deblurring method of Deep Learning,and proposes a fuzzy license plate image restoration method based on Generative Adversarial Network.The main idea is to use the NAFBlock in the image restoration network NAFNet to replace the basic convolution block in the DeblurGAN-v2 generator,and an Efficient Channel Attention mechanism is added to the feature extraction network.For the original model and the modified model,four groups of different model ablation experiments are designed.The experiment results show that the proposed method has a peak signal-to-noise ratio of 21.262 4 and a structural similarity index of 0.643 1 on the task data of restoring blurred vehicle image restoration,which better solves the problem of blurred license plate restoration.
万方数据
维普
