Learning Iterative Image Reconstruction

Sven Behnke

Abstract: Successful image reconstruction requires the recognition of a scene and the generation of a clean image of that scene. In this chapter, I show how to use Neural Abstraction Pyramid networks for both analysis and synthesis of images. The networks have a hierarchical architecture which represents images in multiple scales with different degrees of abstraction. The mapping between these representations is mediated by a local recurrent connection structure.