Spatial Resolution Enhancement of Remote Sensing Mine Images using Deep Learning Techniques

TL;DR

This paper applies deep learning models VDSR and DSen2 to enhance the spatial resolution of Sentinel2 satellite images of a lignite mine, achieving significant resolution improvements and demonstrating the effectiveness of these techniques.

Contribution

The study introduces the use of VDSR and DSen2 deep learning models for resolution enhancement of satellite images, achieving up to 6x resolution improvements.

Findings

Resolution enhancement factors of 2, 4, and 6 achieved

Deep learning models provide good quality results

Effective application to lignite mine satellite imagery

Abstract

Deep learning techniques are applied so as to increase the spatial resolution of Sentinel2 satellite imagery, depicting the Amynteo lignite mine in Ptolemaida, Greece. Resolution enhancement by factors 2 and 4 as well as by factors 2 and 6 using Very-Deep SuperResolution (VDSR) and DSen2 networks, respectively, provides fairly well results on Amynteo lignite mine images.