# Advances on CNN-based super-resolution of Sentinel-2 images

arXiv: https://arxiv.org/abs/1902.02513 · HTML: https://mlsanity.com/paper/1902.02513/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Feb 2019.

## Built on by (most cited first, 1 of 1)

- [Advancing Image Super-resolution Techniques in Remote Sensing: A Comprehensive Survey](https://mlsanity.com/paper/2505.23248/) (2025)

## Abstract (arXiv)

Thanks to their temporal-spatial coverage and free access, Sentinel-2 images are very interesting for the community. However, a relatively coarse spatial resolution, compared to that of state-of-the-art commercial products, motivates the study of super-resolution techniques to mitigate such a limitation. Specifically, thirtheen bands are sensed simultaneously but at different spatial resolutions: 10, 20, and 60 meters depending on the spectral location. Here, building upon our previous convolutional neural network (CNN) based method, we propose an improved CNN solution to super-resolve the 20-m resolution bands benefiting spatial details conveyed by the accompanying 10-m spectral bands.