Hyperspectral Imaging

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9 papers in the last four weeks, down 44% on the four weeks before. 0.1% of all new papers.

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LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift
May 18, 2026Haozhe Si, Yuxuan Wan, Yuqing Wang +2Representation Learning Masked Autoencoders
Department of Electrical and Computer Engineering · 2Siebel School of Computing and Data Science
HyperVision: A Channel-Adaptive Ground-Based Hyperspectral Vision Pre-trained Backbone
May 17, 2026Guanyiman Fu, Jingtao Li, Zihang Cheng +8Vision Foundation Model Adaptation Hyperspectral Imaging
Griffith University, Australia · Wuhan University, China · Nanjing University of Science and Technology, China +2
ChronoEarth-492K: A Large Scale and Long Horizon Spatiotemporal Hyperspectral Earth Observation Dataset and Benchmark
May 15, 2026Haozhe Si, Yuxuan Wan, Yuqing Wang +2Geospatial Foundation Models Self-Supervised Time Series Representation Learning
Department of Electrical and Computer Engineering · Siebel School of Computing and Data Science University of Illinois Urbana-Champaign, IL, USA
AnyBand-Diff: A Unified Remote Sensing Image Generation and Band Repair Framework with Spectral Priors
May 14, 2026Zuopeng Zhao, Ying Liu, Xiaoyu Li +3Diffusion Model Guidance Image Generation
School of Computer Science and Technology / School of Artificial Intelligence, China University of Mining and Technology, Xuzhou, China · Mine Digitization Engineering Research Center of the Ministry of Education, Xuzhou, China · Jiangsu Provincial Industrial Technology Engineering Center for Intelligent Sensing and Emergency IoT in Underground Space, Xuzhou, China
FSCM: Frequency-Enhanced Spatial-Spectral Coupled Mamba for Infrared Hyperspectral Image Colorization
May 13, 2026Tingting Liu, Yuan Liu, Guiping Chen +2Hyperspectral Imaging Visual SSMs
School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing, 210094, China · School of Mechanical Engineering, University of Science and Technology Beijing, Beijing, 100083, China · School of Instrument and Electronics, North University of China, Taiyuan, 030051, China
HADAR-Based Thermal Infrared Hyperspectral Image Restoration
May 13, 2026Cheng Dai, Jiale Lin, Bingxuan Song +4Thermal Imaging Physics-Guided Image Restoration
School of Science, Westlake University, Hangzhou 310030, China
Phy-CoSF: Physics-Guided Continuous Spectral Fields Reconstruction and Super-Resolution for Snapshot Compressive Imaging
May 13, 2026Wudi Chen, Zhiyuan Zha, Xin Yuan +6Image Reconstruction Hyperspectral Image Super-Resolution
College of Communication Engineering, Jilin University, Changchun 130012, China. · School of Engineering, Westlake University, Hangzhou, Zhejiang 310024, China. · School of Electrical & Electronic Engineering, Nanyang Technological University, Singapore 639798. +4
HIR-ALIGN: Enhancing Hyperspectral Image Restoration via Diffusion-Based Data Generation
May 13, 2026Li Pang, Heng Zhao, Yijia Zhang +2Synthetic Data Augmentation Unsupervised Domain Adaptation
Color Constancy in Hyperspectral Imaging via Reduced Spectral Spaces
May 13, 2026G. Dofri Vidarsson, Liying Lu, Sabine SüsstrunkHyperspectral Imaging Inverse Dimensionality Reduction
Ecole Polytechnique Fédérale de Lausanne (EPFL), Lausanne, Switzerland
Adaptive 3D Convolution for Remote Sensing Image Fusion
May 10, 2026Siran Peng, Xiangyu Zhu, Shang-Qi Deng +2Remote Sensing Hyperspectral Imaging
State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences (CASIA), Beijing 100190, China · School of Artificial Intelligence, University of Chinese Academy of Sciences (UCAS), Beijing 100049, China · State Key Laboratory of Human-Machine Hybrid Augmented Intelligence, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University, Xi’an 710049, No.28 Xianning West Road, China +2
R2H-Diff: Guided Spectral Diffusion Model for RGB-to-Hyperspectral Reconstruction
May 7, 2026Songyu Ding, Ronggiang Zhao, Mingchun Sun +1Hyperspectral Imaging Diffusion-Based Inverse Problems
Faculty of Computing, Harbin Institute of Technology, Harbin 150001, China · State Key Laboratory of Smart Farm Technologies and Systems, Harbin 150001, China
Physics-Guided Regime Unmixing
May 5, 2026Paula Pacheco, Pablo Granitto, Juan B. CabralHyperspectral Imaging Physics-Informed ML
GVT-CONAE, Centro Espacial Teófilo Tabanera, Argentina · CONICET, Argentina · FAMAF-UNC, Córdoba, Argentina +1
FUN: A Focal U-Net Combining Reconstruction and Object Detection for Snapshot Spectral Imaging
Apr 30, 2026Dahua Gao, Yubo Dong, Anqi Li +4Multispectral Object Detection Image Reconstruction
School of Artificial Intelligence, Xidian University, Xi’an 710126, China · Changzhi Medical College, the Engineering Research Centre for Intelligent Data Assisted Diagnosis and Treatment in Shanxi Province, and Uniwave Artificial Intelligence Technology Co., Ltd., Changzhi 046000, China
Hyperspectral Image Classification via Efficient Global Spectral Supertoken Clustering
Apr 30, 2026Peifu Liu, Tingfa Xu, Jie Wang +3Soft-Label Learning Hyperspectral Imaging
Beijing Institute of Technology, Beijing 100081, China · Beijing Institute of Technology Chongqing Innovation Center, Chongqing 401135, China · Key Laboratory of Photoelectronic Imaging Technology and System, Ministry of Education of China, Beijing 100081, China
Spectral Dynamic Attention Network for Hyperspectral Image Super-Resolution
Apr 30, 2026Tengya Zhang, Feng Gao, Lin Qi +2Hyperspectral Image Super-Resolution Hyperspectral Imaging
Sanya Oceanographic Institution, Ocean University of China, Sanya, China · State Key Laboratory of Physical Oceanography, Ocean University of China, Qingdao 266100, China · Department of Electrical and Computer Engineering, Mississippi State University, Starkville, MS 39762 USA
Cross-Domain Transfer of Hyperspectral Foundation Models
Apr 29, 2026Nick Theisen, Peer NeubertRemote Sensing Image Segmentation Hyperspectral Imaging
Intelligent Autonomous Systems, University of Koblenz, Germany
MixerCA: An Efficient and Accurate Model for High-Performance Hyperspectral Image Classification
Apr 28, 2026Mohammed Q. Alkhatib, Ali JamaliHyperspectral Imaging Efficient Attention
aCollege of Engineering and IT, University of Dubai, Dubai, 14143, UAE · bDepartment of Geography, Simon Fraser University, 8888 University Dr, Burnaby, BC V5A 1S6, Canada
HyperFM: An Efficient Hyperspectral Foundation Model with Spectral Grouping
Apr 22, 2026Zahid Hassan Tushar, Sanjay PurushothamRemote Sensing Hyperspectral Imaging
University of Maryland, Baltimore County Baltimore, MD, USA
Semi-Supervised Flow Matching for Mosaiced and Panchromatic Fusion Imaging
Apr 22, 2026Peiming Luo, Nan Wang, Litong Liu +4Flow Matching Multi-Source Image Fusion
Southeast University · Hunan University
Voronoi-guided Bilateral 2D Gaussian Splatting for Arbitrary-Scale Hyperspectral Image Super-Resolution
Apr 20, 2026Jie Zhang, Jinkun You, Shi Chen +1Hyperspectral Image Super-Resolution Hyperspectral Imaging
Department of Computer and Information Science University of Macau Macau, China
Self-Supervised Super-Resolution for Sentinel-5P Hyperspectral Images
Apr 19, 2026Hyam Omar Ali, Antoine Crosnier, Romain Abraham +3Self-Supervised Learning Remote Sensing Image Super-Resolution
Université d’Orléans, Université de Tours, CNRS, IDP, UMR 7013, Orléans, France · Faculty of Mathematical Sciences, University of Khartoum, Sudan · ENS Lyon, France +2
HyKey: Hyperspectral Keypoint Detection and Matching in Minimally Invasive Surgery
Apr 19, 2026Alexander Saikia, Chiara Di Vece, Zhehua Mao +63D Reconstruction Hyperspectral Imaging
UCL Hawkes Institute, Dept of Medical Physics and Biomedical Engineering and Dept of Computer Science, University College London, London, WC1E 6BT, United Kingdom. · EnAcuity Ltd., London, EC2A 4NE, United Kingdom.
Hyperspectral Unmixing Hierarchies
Apr 18, 2026Joseph L. Garrett, P. S. Vishnu, Pauliina Salmi +4Non-Negative Matrix Factorization Remote Sensing
Department of Engineering Cybernetics, Norwegian University of Science and Technology · Department of Biology, Norwegian University of Science and Technology · Department of Automatic Control and Systems Engineering, University Politehnica Bucharest +1
SSFT: A Lightweight Spectral-Spatial Fusion Transformer for Generic Hyperspectral Classification
Apr 17, 2026Alexander Musiat, Nikolas Ebert, Oliver WasenmüllerRepresentation Learning Hyperspectral Imaging
Mannheim University of Applied Sciences, Germany
Deep Spatially-Regularized and Superpixel-Based Diffusion Learning for Unsupervised Hyperspectral Image Clustering
Apr 14, 2026Vutichart Buranasiri, James M. MurphyClustering Image Clustering
Department of Mathematics, Tufts University, Medford, MA 02155, USA
Beyond Reconstruction: Reconstruction-to-Vector Diffusion for Hyperspectral Anomaly Detection
Apr 13, 2026Jijun Xiang, Tao Wang, Jiayi Wang +3Anomaly Detection Hyperspectral Imaging
Rocket Force University of Engineering, Xi’an 710025, China
A Deep Equilibrium Network for Hyperspectral Unmixing
Apr 13, 2026Chentong Wang, Jincheng Gao, Fei Zhu +1Hyperspectral Imaging
Center for Applied Mathematics, KL-AAGDM, Tianjin University, Tianjin 300072, China · School of Artiﬁcial Intelligence, Northwestern Polytechnical University, Xi’an 710072, China · National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology
Unmixing-Guided Spatial-Spectral Mamba with Clustering Tokens for Hyperspectral Image Classification
Apr 10, 2026Yimin Zhu, Lincoln Linlin XuHyperspectral Image Classification Hyperspectral Imaging
Department of Geomatics Engineering, University of Calgary, Canada
Beyond RGB: Benchmarking and Enhancing MLLMs for Hyperspectral Image Understanding via Training-Free Reasoning Framework
Apr 10, 2026Xinyu Zhang, Zurong Mai, Qingmei Li +13Multimodal Large Language Models VLM Reasoning
Sun Yat-sen University · Tsinghua Shenzhen International Graduate School · Southwest University +3
MVOS_HSI: A Python Library for Preprocessing Agricultural Crop Hyperspectral Data
Apr 8, 2026Rishik Aggarwal, Krisha Joshi, Pappu Kumar Yadav +3Scientific Workflow Automation Hyperspectral Imaging
Machine Vision and Optical Sensor (MVOS) Lab, Dept. of Agricultural and Biosystems Engineering, South Dakota State University, Brookings, SD 57007, USA · USDA/ARS Environmental Microbial and Food Safety Laboratory, Beltsville, MD 20705, USA · Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA

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LESSViT: Robust Hyperspectral Representation Learning under Spectral Configuration Shift

Haozhe Si, Yuxuan Wan, Yuqing Wang, Minh Do+1

Department of Electrical and Computer Engineering · 2Siebel School of Computing and Data Science

Representation Learning Masked Autoencoders Hyperspectral Imaging Efficient ViTs

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Modeling hyperspectral imagery (HSI) across different sensors presents a fundamental challenge due to variations in wavelength coverage, band sampling, and channel dimensionality. As a result, models trained under a fixed spectral configuration often fail to generalize to other sensors. Existing Vision Transformer (ViT) approaches either rely on implicit spectral modeling with fixed channel assumptions or adopt explicit spatial-spectral attention with prohibitive computational cost, leading to a fundamental trade-off between efficiency and expressiveness. In this work, we introduce Low-rank Efficient Spatial-Spectral ViT (LESSViT), a sensor-flexible architecture for cross-spectral generalization. LESSViT is built on LESS Attention, a structured low-rank factorization that models joint spatial-spectral interactions through separable spatial and spectral components, reducing the complexity of full spatial-spectral attention from

O(N^2 C^2)

O(rNC)

, where

N

is the number of spatial tokens,

C

is the number of spectral channels, and

r

is the rank of the low-rank approximation. We further incorporate channel-agnostic patch embedding and wavelength-aware positional encoding to support flexible spectral inputs. To enable efficient and robust pretraining, we introduce a hyperspectral masked autoencoder (HyperMAE) with decoupled spatial-spectral masking and hierarchical channel sampling. We evaluate LESSViT under a cross-spectral generalization setting that simulates cross-sensor variability. Experiments on the SpectralEarth benchmark demonstrate that LESSViT improves robustness under spectral shifts while remaining competitive in-distribution, and explicit and efficient spatial-spectral modeling is essential for scalable and generalizable hyperspectral representation learning.