LoGSRN: Deep Super Resolution Network for Digital Elevation Model
Catapult co-author: Stephen Spittle
Abstract: The spatial resolution of a Digital Elevation Model (DEM) plays a crucial role in many practical remote sensing applications. However, it is normally limited by the spatial resolution of the raw input imagery, from which a DEM is derived. One solution to enhance the limited resolution of a DEM during the post-processing, is fusing previously obtained high resolution DEM data. This data-driven approach appears particularly promising, considering the recent success of a deep convolutional network in single image super resolution (SISR). In this paper, we propose a new SISR network that can recover a high resolution DEM.