English

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

Image and Video Processing 2020-07-20 v1 Machine Learning
Authors: E. Zioga , A. Panagiotopoulou , M. Stefouli , E. Charou , L. Grammatikopoulos , E. Bratsolis , N. Madamopoulos
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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.

Cite

@article{arxiv.2007.08791,
  title  = {Spatial Resolution Enhancement of Remote Sensing Mine Images using Deep Learning Techniques},
  author = {E. Zioga and A. Panagiotopoulou and M. Stefouli and E. Charou and L. Grammatikopoulos and E. Bratsolis and N. Madamopoulos},
  journal= {arXiv preprint arXiv:2007.08791},
  year   = {2020}
}

Comments

5 pages, 4 figures, presented in 2nd Greek Remote Sensing Workshop RSSAC2020

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