SR4RS: A Tool for Super Resolution of Remote Sensing Images

Rémi Cresson

doi:10.5334/jors.369

SR4RS: A Tool for Super Resolution of Remote Sensing Images

Journal of Open Research Software

Volume 10 (2022): Issue 1

By: Rémi Cresson

Open Access

|Mar 2022

Abstract

The SR4RS software includes tools to apply super-resolution methods on remote sensing images. It employs TensorFlow on the deep learning side, and relies on GDAL and the Orfeo ToolBox to deal with geospatial data. The software is written in simple python, and provides user-oriented applications to train and apply state of the art models on images.

References

Ledig C, Theis L, Huszár F, Caballero J, Cunningham A, Acosta A, Shi W. Photo-realistic single image super-resolution using a generative adversarial network. In Proceedings of the IEEE conference on computer vision and pattern recognition. 2017; 4681–4690. DOI: 10.1109/CVPR.2017.19
Open DOI Search in Google Scholar Back to article
Karras T, et al. “Progressive growing of gans for improved quality, stability, and variation.” arXiv preprint arXiv:1710.10196; 2017.
Search in Google Scholar Back to article
Karnewar A, Wang, O. Msg-gan: Multi-scale gradients for generative adversarial networks. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2020; 7799–7808. DOI: 10.1109/CVPR42600.2020.00782
Open DOI Search in Google Scholar Back to article
Warmerdam F. The geospatial data abstraction library. In Open source approaches in spatial data handling. 2008; 87–104. Berlin, Heidelberg: Springer. DOI: 10.1007/978-3-540-74831-1_5
Open DOI Search in Google Scholar Back to article
Grizonnet M, Michel J, Poughon V, Inglada J, Savinaud M, Cresson R. Orfeo ToolBox: open source processing of remote sensing images. Open Geospatial Data, Software and Standards. 2017; 2(1): 1–8. DOI: 10.1186/s40965-017-0031-6
Open DOI Search in Google Scholar Back to article
Abadi M, Barham P, Chen J, Chen Z, Davis A, Dean J, …, Zheng X. Tensorflow: A system for large-scale machine learning. In 12th USENIX symposium on operating systems design and implementation (OSDI 16). 2016; 265–283.
Search in Google Scholar Back to article