MLSA-UNET: End-To-End Multi-Level Spatial Attention Guided Unet For industrial Defect Segmentation

High-speed is an essential requirement for many applications of image registration. However, existing methods are usually time-consuming due to the difficulty of the task. in this paper, different from usual feature-based ideas, we convert the matching problem into an algebraic optimization task. By solving a series of quadratic optimization equations, the underlying deformation (rotation, scaling and shift) between image pairs can be retrieved. This process is extremely fast and can be performed in real-time. Experiments show that our method can achieve good performance at a much lower computation cost. When used to initialize our earlier parametric Local All-Pass (LAP) registration algorithm, the results obtained improve significantly over the state of the art.