Unsupervised Learning of High-resolution Light Field Imaging via Beam Splitter-based Hybrid Lenses

The author presents an unsupervised learning-based approach for spatial super-resolution in light field imaging using a hybrid system, overcoming the limitations of ground truth data. By designing a beam splitter-based hybrid system and proposing novel loss functions, the method achieves superior performance compared to state-of-the-art supervised methods.