Research on sonar image generation technique based on improved CycleGAN

Aiming at the problems of insufficient data volume and scarcity of target images in the target detection task of sonar images, this paper proposes an image style migration from optical to acoustic based on an improved cyclegan method based on the imaging principle and process of side-scan sonar images to realize the acoustic database augmentation so as to improve the status quo of the scarce number of samples of sonar images. In this paper, we enhance the feature extraction capability of the model network by introducing the cbam attention module to the original cyclegan generator, and evaluate the migration effect using the image quality assessment metrics is and fid. The experimental results conducted with the traditional method show that the method introducing the cbam attention mechanism module has a better style migration effect for sonar image generation.