mlsanityData to 7 Oct 2026

RSDiff: Remote Sensing Image Generation from Text Using Diffusion Model

arXiv 2309.02455 ↗First posted 3 Sep 2023cs.CVcited by 28

On the map: Diffusion models → Inverse problems and image restoration

Abstract (arXiv)

The generation and enhancement of satellite imagery are critical in remote sensing, requiring high-quality, detailed images for accurate analysis. This research introduces a two-stage diffusion model methodology for synthesizing high-resolution satellite images from textual prompts. The pipeline comprises a Low-Resolution Diffusion Model (LRDM) that generates initial images based on text inputs and a Super-Resolution Diffusion Model (SRDM) that refines these images into high-resolution outputs. The LRDM merges text and image embeddings within a shared latent space, capturing essential scene content and structure. The SRDM then enhances these images, focusing on spatial features and visual clarity. Experiments conducted using the Remote Sensing Image Captioning Dataset (RSICD) demonstrate that our method outperforms existing models, producing satellite images with accurate geographical details and improved spatial resolution.

Key facts. Cited by 28 papers in the map (data through 7 Oct 2026). Placed in Inverse problems and image restoration, one of 14 directions in Diffusion models. Builds on 33 of its 50 references that are in the map. First posted on arXiv 3 Sep 2023.

Builds on

33 of 50 references.

Closest ancestors · 1

Same direction, newest first

  1. 2021Deblurring via Stochastic Refinement5 Dec

Other references · 32

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  3. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  4. 2020Language Models are Few-Shot Learnerscited by 32,199
  5. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  6. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  7. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  8. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  9. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  10. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  11. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  12. 2022Classifier-Free Diffusion Guidancecited by 5,717
20 more
  1. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  2. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  3. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  4. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
  5. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  6. 2016Improved Techniques for Training GANscited by 2,938
  7. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  8. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  9. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,155
  10. 2018Adafactor: Adaptive Learning Rates with Sublinear Memory Costcited by 896
  11. 2017AttnGAN: Fine-Grained Text to Image Generation with Attentional Generative Adversarial Networkscited by 664
  12. 2016StackGAN: Text to Photo-realistic Image Synthesis with Stacked Generative Adversarial Networkscited by 575
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  14. 2017Exploring Models and Data for Remote Sensing Image Caption Generationcited by 195
  15. 2020DF-GAN: A Simple and Effective Baseline for Text-to-Image Synthesiscited by 161
  16. 2016Learning What and Where to Drawcited by 105
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  18. 2021DAE-GAN: Dynamic Aspect-aware GAN for Text-to-Image Synthesiscited by 45
  19. 2022Txt2Img-MHN: Remote Sensing Image Generation from Text Using Modern Hopfield Networkscited by 28
  20. 2022Universal Adversarial Examples in Remote Sensing: Methodology and Benchmarkcited by 24

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 1; 2024: 7; 2025: 12; 2026: 8.

28 papers.

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  1. 2024CRS-Diff: Controllable Remote Sensing Image Generation with Diffusion Modelcited by 54
  2. 2025Text2Earth: Unlocking Text-driven Remote Sensing Image Generation with a Global-Scale Dataset and a Foundation Modelcited by 46
  3. 2023Learned representation-guided diffusion models for large-image generationcited by 39
  4. 2024Diffusion Models Meet Remote Sensing: Principles, Methods, and Perspectivescited by 27
  5. 2025A Survey on Remote Sensing Foundation Models: From Vision to Multimodalitycited by 18
  6. 2025Vision-Language Modeling Meets Remote Sensing: Models, Datasets and Perspectivescited by 18
  7. 2024ZoomLDM: Latent Diffusion Model for multi-scale image generationcited by 15
  8. 2024Detecting Out-Of-Distribution Earth Observation Images with Diffusion Modelscited by 14
  9. 2024Data Augmentation in Earth Observation: A Diffusion Model Approachcited by 7
  10. 2024CC-Diff: Enhancing Contextual Coherence in Remote Sensing Image Synthesiscited by 7
  11. 2025Multimodal LLM-Guided Semantic Correction in Text-to-Image Diffusioncited by 5
  12. 2025Object Fidelity Diffusion for Remote Sensing Image Generationcited by 4
16 more
  1. 2025RS-Prune: Training-Free Data Pruning at High Ratios for Efficient Remote Sensing Diffusion Foundation Modelscited by 4
  2. 2024MMO-IG: Multi-Class and Multi-Scale Object Image Generation for Remote Sensingcited by 2
  3. 2025EarthMapper: Visual Autoregressive Models for Controllable Bidirectional Satellite-Map Translationcited by 2
  4. 2026Location Is All You Need: Continuous Spatiotemporal Neural Representations of Earth Observation Datacited by 2
  5. 2025MGCR-Net:Multimodal Graph-Conditioned Vision-Language Reconstruction Network for Remote Sensing Change Detectioncited by 1
  6. 2025Lesion-Aware Post-Training of Latent Diffusion Models for Synthesizing Diffusion MRI from CT Perfusioncited by 1
  7. 2025Environment-Aware Satellite Image Generation with Diffusion Modelscited by 0
  8. 2025Discrete Wavelet Transform as a Facilitator for Expressive Latent Space Representation in Variational Autoencoders in Satellite Imagerycited by 0
  9. 2025LC4-DViT: Land-cover Creation for Land-cover Classification with Deformable Vision Transformercited by 0
  10. 2026Mitigating Long-Tail Bias via Prompt-Controlled Diffusion Augmentationcited by 0
  11. 2026Earth Science Foundation Models: From Perception to Reasoning and Discoverycited by 0
  12. 2026D2-CDIG: Controlled Diffusion Remote Sensing Image Generation with Dual Priors of DEM and Cloud-Fogcited by 0
  13. 2026AnyBand-Diff: A Unified Remote Sensing Image Generation and Band Repair Framework with Spectral Priorscited by 0
  14. 2026MetaEarth-MM: Unified Multimodal Remote Sensing Image Generation with Scene-centered Joint Modelingcited by 0
  15. 2026GeoCore-9B: Towards Geo-Aware Generative Foundation Models in Earth Observationcited by 0
  16. 2026Real-World Knowledge-Guided Change Data Synthesis for Remote Sensingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023DiffusionSat: A Generative Foundation Model for Satellite Imagery
  2. 2024MMM-RS: A Multi-modal, Multi-GSD, Multi-scene Remote Sensing Dataset and Benchmark for Text-to-Image Generation
  3. 2024Remote Diffusion
  4. 2026SlimDiffSR: Toward Lightweight and Efficient Remote Sensing Image Super-Resolution via Diffusion Model Distillation
  5. 2024Semantic Guided Large Scale Factor Remote Sensing Image Super-resolution with Generative Diffusion Prior
  6. 2024Diffusion-RSCC: Diffusion Probabilistic Model for Change Captioning in Remote Sensing Images
  7. 2025Metadata, Wavelet, and Time Aware Diffusion Models for Satellite Image Super Resolution
  8. 2024SatDiffMoE: A Mixture of Estimation Method for Satellite Image Super-resolution with Latent Diffusion Models