Traffic image deblurring method and device based on multi-scale adversarial learning
A deblurring and multi-scale technology, applied in the field of artificial intelligence technology and image restoration, can solve problems such as poor restoration of detail information, and achieve the effect of improving generation quality, improving restoration quality, and good generalization ability
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[0044] Below in conjunction with accompanying drawing, further describe the present invention through embodiment, but do not limit the scope of the present invention in any way.
[0045] figure 1 In order to show an overall flowchart of a traffic image deblurring method based on multi-scale confrontation learning according to an example, it specifically includes the following steps:
[0046] Step 1: Use the motion blur dataset generation method to generate clear-blurred traffic image pairs;
[0047] Step 2: Build a traffic image deblurring network model based on adversarial learning, and perform adversarial learning on the restored image to make it closer to the real clear image;
[0048] Step 3: Construct multiple image deblurring network models with the same structure from small to large scales, pass the recovered clear images at small scales as input to the subsequent network, restore them scale by scale, and finally obtain the deblurred image of the original size;
[004...
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