# HSR-Diff:Hyperspectral Image Super-Resolution via Conditional Diffusion Models

arXiv: https://arxiv.org/abs/2306.12085 · HTML: https://mlsanity.com/paper/2306.12085/

## Key facts

- Cited by 31 papers in the map (data through 14 Oct 2026).
- Placed in Inverse problems and image restoration, one of 14 directions in Diffusion models.
- Builds on 29 of its 57 references that are in the map.
- First posted on arXiv 21 Jun 2023.

## Placed in

- Diffusion models / [Inverse problems and image restoration](https://mlsanity.com/diffusion/inverse-problems-and-image-restoration/)

## Builds on (most cited first, 29 of 29)

- [Denoising Diffusion Probabilistic Models](https://mlsanity.com/paper/2006.11239/) (2020)
- [Swin Transformer: Hierarchical Vision Transformer using Shifted Windows](https://mlsanity.com/paper/2103.14030/) (2021)
- [Generative Adversarial Networks](https://mlsanity.com/paper/2203.00667/) (2022)
- [Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification](https://mlsanity.com/paper/1502.01852/) (2015)
- [Improved Training of Wasserstein GANs](https://mlsanity.com/paper/1704.00028/) (2017)
- [Variational Inference with Normalizing Flows](https://mlsanity.com/paper/1505.05770/) (2015)
- [Density estimation using Real NVP](https://mlsanity.com/paper/1605.08803/) (2016)
- [Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network](https://mlsanity.com/paper/1609.04802/) (2016)
- [Restormer: Efficient Transformer for High-Resolution Image Restoration](https://mlsanity.com/paper/2111.09881/) (2021)
- [Glow: Generative Flow with Invertible 1x1 Convolutions](https://mlsanity.com/paper/1807.03039/) (2018)
- [Image Super-Resolution via Iterative Refinement](https://mlsanity.com/paper/2104.07636/) (2021)
- [Image Super-Resolution Using Deep Convolutional Networks](https://mlsanity.com/paper/1501.00092/) (2014)
- [Pixel Recurrent Neural Networks](https://mlsanity.com/paper/1601.06759/) (2016)
- [CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classification](https://mlsanity.com/paper/2103.14899/) (2021)
- [NVAE: A Deep Hierarchical Variational Autoencoder](https://mlsanity.com/paper/2007.03898/) (2020)
- [WaveGrad: Estimating Gradients for Waveform Generation](https://mlsanity.com/paper/2009.00713/) (2020)
- [PixelCNN++: Improving the PixelCNN with Discretized Logistic Mixture Likelihood and Other Modifications](https://mlsanity.com/paper/1701.05517/) (2017)
- [Open-Vocabulary Panoptic Segmentation with Text-to-Image Diffusion Models](https://mlsanity.com/paper/2303.04803/) (2023)
- [Material Based Object Tracking in Hyperspectral Videos: Benchmark and Algorithms](https://mlsanity.com/paper/1812.04179/) (2018)
- [Fusformer: A Transformer-based Fusion Approach for Hyperspectral Image Super-resolution](https://mlsanity.com/paper/2109.02079/) (2021)
- [Unsupervised Sparse Dirichlet-Net for Hyperspectral Image Super-Resolution](https://mlsanity.com/paper/1804.05042/) (2018)
- [Hyperspectral and Multispectral Image Fusion based on a Sparse Representation](https://mlsanity.com/paper/1409.5729/) (2014)
- [Coupled Convolutional Neural Network with Adaptive Response Function Learning for Unsupervised Hyperspectral Super-Resolution](https://mlsanity.com/paper/2007.14007/) (2020)
- [Synthetic Data Supervised Salient Object Detection](https://mlsanity.com/paper/2210.13835/) (2022)
- [A Latent Encoder Coupled Generative Adversarial Network (LE-GAN) for Efficient Hyperspectral Image Super-resolution](https://mlsanity.com/paper/2111.08685/) (2021)
- [Super-Resolution for Hyperspectral and Multispectral Image Fusion Accounting for Seasonal Spectral Variability](https://mlsanity.com/paper/1808.10072/) (2018)
- [3D-ANAS: 3D Asymmetric Neural Architecture Search for Fast Hyperspectral Image Classification](https://mlsanity.com/paper/2101.04287/) (2021)
- [Hyperspectral Image Super-resolution with Deep Priors and Degradation Model Inversion](https://mlsanity.com/paper/2201.09851/) (2022)
- [Grafting Transformer on Automatically Designed Convolutional Neural Network for Hyperspectral Image Classification](https://mlsanity.com/paper/2110.11084/) (2021)

## Built on by (most cited first, 30 of 31)

- [Diffusion Models for Image Restoration and Enhancement: A Comprehensive Survey](https://mlsanity.com/paper/2308.09388/) (2023)
- [Diffusion Models in Low-Level Vision: A Survey](https://mlsanity.com/paper/2406.11138/) (2024)
- [CRS-Diff: Controllable Remote Sensing Image Generation with Diffusion Model](https://mlsanity.com/paper/2403.11614/) (2024)
- [UniGS: Unified Representation for Image Generation and Segmentation](https://mlsanity.com/paper/2312.01985/) (2023)
- [Unsupervised Hyperspectral Image Super-Resolution via Self-Supervised Modality Decoupling](https://mlsanity.com/paper/2412.04802/) (2024)
- [Building Bridges across Spatial and Temporal Resolutions: Reference-Based Super-Resolution via Change Priors and Conditional Diffusion Model](https://mlsanity.com/paper/2403.17460/) (2024)
- [A Comprehensive Survey for Hyperspectral Image Classification: The Evolution from Conventional to Transformers and Mamba Models](https://mlsanity.com/paper/2404.14955/) (2024)
- [Unaligned RGB Guided Hyperspectral Image Super-Resolution with Spatial-Spectral Concordance](https://mlsanity.com/paper/2505.02109/) (2025)
- [ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolution](https://mlsanity.com/paper/2307.00781/) (2023)
- [FocusDiffuser: Perceiving Local Disparities for Camouflaged Object Detection](https://mlsanity.com/paper/2407.13133/) (2024)
- [On Improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models](https://mlsanity.com/paper/2411.03177/) (2024)
- [A Spectral Diffusion Prior for Hyperspectral Image Super-Resolution](https://mlsanity.com/paper/2311.08955/) (2023)
- [Image is All You Need to Empower Large-scale Diffusion Models for In-Domain Generation](https://mlsanity.com/paper/2312.08195/) (2023)
- [MP-HSIR: A Multi-Prompt Framework for Universal Hyperspectral Image Restoration](https://mlsanity.com/paper/2503.09131/) (2025)
- [Unpaired Volumetric Harmonization of Brain MRI with Conditional Latent Diffusion](https://mlsanity.com/paper/2408.09315/) (2024)
- [Hipandas: Hyperspectral Image Joint Denoising and Super-Resolution by Image Fusion with the Panchromatic Image](https://mlsanity.com/paper/2412.04201/) (2024)
- [NeurOp-Diff:Continuous Remote Sensing Image Super-Resolution via Neural Operator Diffusion](https://mlsanity.com/paper/2501.09054/) (2025)
- [RoofDiffusion: Constructing Roofs from Severely Corrupted Point Data via Diffusion](https://mlsanity.com/paper/2404.09290/) (2024)
- [Neural Shr"odinger Bridge Matching for Pansharpening](https://mlsanity.com/paper/2404.11416/) (2024)
- [HSR-KAN: Efficient Hyperspectral Image Super-Resolution via Kolmogorov-Arnold Networks](https://mlsanity.com/paper/2409.06705/) (2024)
- [Parasite: A Steganography-based Backdoor Attack Framework for Diffusion Models](https://mlsanity.com/paper/2504.05815/) (2025)
- [Diffusion Models for Hyperspectral Image Analysis: A Comprehensive Review](https://mlsanity.com/paper/2505.11158/) (2025)
- [AI-Driven HSI: Multimodality, Fusion, Challenges, and the Deep Learning Revolution](https://mlsanity.com/paper/2502.06894/) (2025)
- [Multispectral Demosaicing via Dual Cameras](https://mlsanity.com/paper/2503.22026/) (2025)
- [GEWDiff: Geometric Enhanced Wavelet-based Diffusion Model for Hyperspectral Image Super-resolution](https://mlsanity.com/paper/2511.07103/) (2025)
- [Degradation Alchemy: Self-Supervised Unknown-to-Known Transformation for Blind Hyperspectral Image Fusion](https://mlsanity.com/paper/2503.14892/) (2025)
- [Environment-Aware Satellite Image Generation with Diffusion Models](https://mlsanity.com/paper/2509.24875/) (2025)
- [Segmentation-Aware Latent Diffusion for Satellite Image Super-Resolution: Enabling Smallholder Farm Boundary Delineation](https://mlsanity.com/paper/2511.14481/) (2025)
- [Uncertainty Quantification in HSI Reconstruction using Physics-Aware Diffusion Priors and Optics-Encoded Measurements](https://mlsanity.com/paper/2511.18473/) (2025)
- [Self-Supervised Super-Resolution for Sentinel-5P Hyperspectral Images](https://mlsanity.com/paper/2604.17652/) (2026)

## Abstract (arXiv)

Despite the proven significance of hyperspectral images (HSIs) in performing various computer vision tasks, its potential is adversely affected by the low-resolution (LR) property in the spatial domain, resulting from multiple physical factors. Inspired by recent advancements in deep generative models, we propose an HSI Super-resolution (SR) approach with Conditional Diffusion Models (HSR-Diff) that merges a high-resolution (HR) multispectral image (MSI) with the corresponding LR-HSI. HSR-Diff generates an HR-HSI via repeated refinement, in which the HR-HSI is initialized with pure Gaussian noise and iteratively refined. At each iteration, the noise is removed with a Conditional Denoising Transformer (CDF ormer) that is trained on denoising at different noise levels, conditioned on the hierarchical feature maps of HR-MSI and LR-HSI. In addition, a progressive learning strategy is employed to exploit the global information of full-resolution images. Systematic experiments have been conducted on four public datasets, demonstrating that HSR-Diff outperforms state-of-the-art methods.