Interactive Editing of Massive Imagery Made Simple: Turning Atlanta Into Atlantis

This simple framework for progressive processing of high-resolution images with minimal resources implements an adaptive, multi-resolution solver for gradient-based image processing that is capable of real-time seamless cloning for images that are hundreds of gigapixels in size.

Brian Summa
University of Utah

Giorgio Scorzelli
University of Utah

Ming Jiang
Lawrence Livermore National Laboratory

Peer-Timo Bremer
University of Utah and Lawrence Livermore National Laboratory

Valerio Pascucci
University of Utah