# Multi-Spectral Multi-Image Super-Resolution of Sentinel-2 with Radiometric Consistency Losses and Its Effect on Building Delineation

arXiv: https://arxiv.org/abs/2111.03231 · HTML: https://mlsanity.com/paper/2111.03231/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 40 references that are in the map.
- First posted on arXiv 5 Nov 2021.

## Builds on (most cited first, 24 of 24)

- [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](https://mlsanity.com/paper/1609.04802/) (2016)
- [Deep High-Resolution Representation Learning for Visual Recognition](https://mlsanity.com/paper/1908.07919/) (2019)
- [ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks](https://mlsanity.com/paper/1809.00219/) (2018)
- [Image Super-Resolution Using Deep Convolutional Networks](https://mlsanity.com/paper/1501.00092/) (2014)
- [Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation](https://mlsanity.com/paper/1909.11065/) (2019)
- [Accelerating the Super-Resolution Convolutional Neural Network](https://mlsanity.com/paper/1608.00367/) (2016)
- [Deep Learning for Image Super-resolution: A Survey](https://mlsanity.com/paper/1902.06068/) (2019)
- [SRFlow: Learning the Super-Resolution Space with Normalizing Flow](https://mlsanity.com/paper/2006.14200/) (2020)
- [Deep Image Homography Estimation](https://mlsanity.com/paper/1606.03798/) (2016)
- [A Deep Journey into Super-resolution: A survey](https://mlsanity.com/paper/1904.07523/) (2019)
- [Handheld Multi-Frame Super-Resolution](https://mlsanity.com/paper/1905.03277/) (2019)
- [Deep Burst Super-Resolution](https://mlsanity.com/paper/2101.10997/) (2021)
- [On hallucinations in tomographic image reconstruction](https://mlsanity.com/paper/2012.00646/) (2020)
- [The Multi-Temporal Urban Development SpaceNet Dataset](https://mlsanity.com/paper/2102.04420/) (2021)
- [The Effects of Super-Resolution on Object Detection Performance in Satellite Imagery](https://mlsanity.com/paper/1812.04098/) (2018)
- [Explorable Super Resolution](https://mlsanity.com/paper/1912.01839/) (2019)
- [HighRes-net: Recursive Fusion for Multi-Frame Super-Resolution of Satellite Imagery](https://mlsanity.com/paper/2002.06460/) (2020)
- [DeepSUM: Deep neural network for Super-resolution of Unregistered Multitemporal images](https://mlsanity.com/paper/1907.06490/) (2019)
- [ColorMapGAN: Unsupervised Domain Adaptation for Semantic Segmentation Using Color Mapping Generative Adversarial Networks](https://mlsanity.com/paper/1907.12859/) (2019)
- [Multi-image Super Resolution of Remotely Sensed Images using Residual Feature Attention Deep Neural Networks](https://mlsanity.com/paper/2007.03107/) (2020)
- [Super-Resolution of PROBA-V Images Using Convolutional Neural Networks](https://mlsanity.com/paper/1907.01821/) (2019)
- [Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V images for Cloud Detection](https://mlsanity.com/paper/2006.05923/) (2020)
- [Estimating Crop Primary Productivity with Sentinel-2 and Landsat 8 using Machine Learning Methods Trained with Radiative Transfer Simulations](https://mlsanity.com/paper/2012.12101/) (2020)
- [Joint Gaussian Processes for Biophysical Parameter Retrieval](https://mlsanity.com/paper/1711.05197/) (2017)

## Built on by (most cited first, 19 of 19)

- [DiffusionSat: A Generative Foundation Model for Satellite Imagery](https://mlsanity.com/paper/2312.03606/) (2023)
- [SuperYOLO: Super Resolution Assisted Object Detection in Multimodal Remote Sensing Imagery](https://mlsanity.com/paper/2209.13351/) (2022)
- [Open High-Resolution Satellite Imagery: The WorldStrat Dataset -- With Application to Super-Resolution](https://mlsanity.com/paper/2207.06418/) (2022)
- [MuS2: A Real-World Benchmark for Sentinel-2 Multi-Image Super-Resolution](https://mlsanity.com/paper/2210.02745/) (2022)
- [Deep Learning for Satellite Image Time Series Analysis: A Review](https://mlsanity.com/paper/2404.03936/) (2024)
- [Multitemporal and multispectral data fusion for super-resolution of Sentinel-2 images](https://mlsanity.com/paper/2301.11154/) (2023)
- [LSwinSR: UAV Imagery Super-Resolution based on Linear Swin Transformer](https://mlsanity.com/paper/2303.10232/) (2023)
- [Advancing Supervised Local Learning Beyond Classification with Long-term Feature Bank](https://mlsanity.com/paper/2406.00446/) (2024)
- [Spiking Meets Attention: Efficient Remote Sensing Image Super-Resolution with Attention Spiking Neural Networks](https://mlsanity.com/paper/2503.04223/) (2025)
- [Continuous Urban Change Detection from Satellite Image Time Series with Temporal Feature Refinement and Multi-Task Integration](https://mlsanity.com/paper/2406.17458/) (2024)
- [Zooming Out on Zooming In: Advancing Super-Resolution for Remote Sensing](https://mlsanity.com/paper/2311.18082/) (2023)
- [Earth System Data Cubes: Avenues for advancing Earth system research](https://mlsanity.com/paper/2408.02348/) (2024)
- [Can Location Embeddings Enhance Super-Resolution of Satellite Imagery?](https://mlsanity.com/paper/2501.15847/) (2025)
- [Toward task-driven satellite image super-resolution](https://mlsanity.com/paper/2503.15474/) (2025)
- [Leveraging Land Cover Priors for Isoprene Emission Super-Resolution](https://mlsanity.com/paper/2503.18658/) (2025)
- [Beyond Pretty Pictures: Combined Single- and Multi-Image Super-resolution for Sentinel-2 Images](https://mlsanity.com/paper/2505.24799/) (2025)
- [Controllable Reference Guided Diffusion with Local Global Fusion for Real World Remote Sensing Image Super Resolution](https://mlsanity.com/paper/2506.23801/) (2025)
- [SatFusion: A Unified Framework for Enhancing Remote Sensing Images via Multi-Frame and Multi-Source Images Fusion](https://mlsanity.com/paper/2510.07905/) (2025)
- [TinyNina: A Resource-Efficient Edge-AI Framework for Sustainable Air Quality Monitoring via Intra-Image Satellite Super-Resolution](https://mlsanity.com/paper/2604.04445/) (2026)

## Abstract (arXiv)

High resolution remote sensing imagery is used in broad range of tasks, including detection and classification of objects. High-resolution imagery is however expensive, while lower resolution imagery is often freely available and can be used by the public for range of social good applications. To that end, we curate a multi-spectral multi-image super-resolution dataset, using PlanetScope imagery from the SpaceNet 7 challenge as the high resolution reference and multiple Sentinel-2 revisits of the same imagery as the low-resolution imagery. We present the first results of applying multi-image super-resolution (MISR) to multi-spectral remote sensing imagery. We, additionally, introduce a radiometric consistency module into MISR model the to preserve the high radiometric resolution of the Sentinel-2 sensor. We show that MISR is superior to single-image super-resolution and other baselines on a range of image fidelity metrics. Furthermore, we conduct the first assessment of the utility of multi-image super-resolution on building delineation, showing that utilising multiple images results in better performance in these downstream tasks.