Fig. 5

The overall Structure of SGRGAN. (a) Generator Details: Achieving simultaneous processing and optimization of image structure information and texture features through a coupled encoder-decoder. (b) Discriminator Details: Utilizing a dual-stream discriminator to estimate texture and structure feature statistics to distinguish between restored and real images. (c) BiSCCFormer Block: A novel module based on a Bi-level routing attention mechanism, facilitating a deeper and more comprehensive understanding of the intrinsic structure and semantic information within images. (d) Focal Block: Utilizing two skip connection structures to expand the receptive field of feature maps, emphasizing feature learning in important areas while combining coarse-grained global data and fine-grained local features. (e) Feature Fusion Block: Deep fusion of extracted texture features and structural features