Using Conditional Adversarial Networks to Deblur the Sonar Image of the Unknown Motion Blur Kernels

Abstract

In order to recover the blurred sonar image collected by the side scan sonar during motion, we propose a solution based on the conditional adversarial networks to deblur the sonar image of the unknown motion blur kernels. First, we use improved conditional adversarial networks to recover the sonar image, and improve the loss function, so that the quality of image generation is improved while the training stability is enhanced. Then we propose a method for generating blurred sonar images. The blurred sonar image generated by this method is closer to the real blurred sonar image. Finally, we made our own sonar image set and trained it with two-timescale update rule. The final results proved that the image restored by this method has higher definition.