Computer Engineering and Applications ›› 2021, Vol. 57 ›› Issue (22): 241-246.DOI: 10.3778/j.issn.1002-8331.2007-0279

• Graphics and Image Processing • Previous Articles     Next Articles

Research on Image Restoration Method Based on Structure Embedding

WANG Haiyong, LI Haiyang, GAO Xuejiao   

  1. School of Electronic and Information Engineering, Lanzhou Jiaotong University, Lanzhou 730070, China
  • Online:2021-11-15 Published:2021-11-16



  1. 兰州交通大学 电子与信息工程学院,兰州 730070


In view of the current problem in the field of image repair, there is a problem of lost structure and blurred texture, and it is not possible to make full use of background information to generate a filled area with a consistent content style. Based on the encoder-decoder network, this paper proposes a shared repair model with multi-scale structure information and attention mechanism. In the generation stage, multi-scale structure information is embedded to provide prerequisites for image restoration. At the same time, the multi-scale attention mechanism is used to obtain relevant information on the background information, and refine the content and structure related to the image. This model uses PatchGAN and fixed-weight VGG-16 classifier as the discriminator, and uses style loss and perception loss to the adversarial network in order to achieve the style consistency of the generated images. Compared with the current  mainstream image repair algorithms on the Places2 dataset, the results show that proposed the algorithm can restore the detailed information about the image structure better than other algorithms, and generate clearer and more detailed repair results.

Key words: Generative Adversarial Networks(GAN), attention mechanism, VGG-16, image repair



关键词: 生成对抗网络(GAN), 注意力机制, VGG-16, 图像修复