mlsanityData to 14 Oct 2026

Improved Flood Insights: Diffusion-Based SAR to EO Image Translation

arXiv 2307.07123 ↗First posted 14 Jul 2023cs.CV eess.IVcited by 5

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Abstract (arXiv)

Driven by rapid climate change, the frequency and intensity of flood events are increasing. Electro-Optical (EO) satellite imagery is commonly utilized for rapid response. However, its utilities in flood situations are hampered by issues such as cloud cover and limitations during nighttime, making accurate assessment of damage challenging. Several alternative flood detection techniques utilizing Synthetic Aperture Radar (SAR) data have been proposed. Despite the advantages of SAR over EO in the aforementioned situations, SAR presents a distinct drawback: human analysts often struggle with data interpretation. To tackle this issue, this paper introduces a novel framework, Diffusion-Based SAR to EO Image Translation (DSE). The DSE framework converts SAR images into EO images, thereby enhancing the interpretability of flood insights for humans. Experimental results on the Sen1Floods11 and SEN12-FLOOD datasets confirm that the DSE framework not only delivers enhanced visual information but also improves performance across all tested flood segmentation baselines.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 13 of its 48 references that are in the map. First posted on arXiv 14 Jul 2023.

Builds on

13 of 48 references.

References · 13

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 9,122
  5. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,253
  6. 2017High-Resolution Image Synthesis and Semantic Manipulation with Conditional GANscited by 1,179
  7. 2018Noise2Noise: Learning Image Restoration without Clean Datacited by 533
  8. 2022BBDM: Image-to-image Translation with Brownian Bridge Diffusion Modelscited by 225
  9. 2023MM-BSN: Self-Supervised Image Denoising for Real-World with Multi-Mask based on Blind-Spot Networkcited by 30
  10. 2022Unsupervised Change Detection Based on Image Reconstruction Losscited by 22
  11. 2022SAR Despeckling using a Denoising Diffusion Probabilistic Modelcited by 19
  12. 2022Self-Pair: Synthesizing Changes from Single Source for Object Change Detection in Remote Sensing Imagerycited by 19
1 more
  1. 2023SAR2EO: A High-resolution Image Translation Framework with Denoising Enhancementcited by 3

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Cited by year

Citing papers per year: 2024: 5.

5 papers.

  1. 2024Diffusion Models in Low-Level Vision: A Surveycited by 74
  2. 2024Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectivescited by 27
  3. 2024C-DiffSET: Leveraging Latent Diffusion for SAR-to-EO Image Translation with Confidence-Guided Reliable Object Generationcited by 8
  4. 2024PBVS 2024 Solution: Self-Supervised Learning and Sampling Strategies for SAR Classification in Extreme Long-Tail Distributioncited by 1
  5. 2024Multi-Sensor Diffusion-Driven Optical Image Translation for Large-Scale Applicationscited by 0