Fig. 2.

Deep learning network architecture. a Overall network architecture, including IW, SAPCD, and RRDAB modules, convolution layers, the skip connection, up-sampling operation, and discriminator. b Image registration framework. Image warping is performed by the ORB feature extraction method to construct the training dataset. The self-alignment pyramid, cascading, and deformable convolutions (SAPCD) are embedded in the generator. c RRDAB reconstruction network. Cascaded RRDAB modules are used for image reconstruction, and dense connectivity DAB for feature communication. The attention blocks consist of two SE modules. DConv: deformable convolution; L: level; LR: low-resolution; HR: high-resolution; DAB: dense attention block; IW: image warp; FA: feature alignment; HR: high resolution; GT: ground truth.