多模态信息融合

Blind Image Fusion for Hyperspectral Imaging with the Directional Total Variation

Leon Bungert, David A. Coomes, Matthias J. Ehrhardt, Jennifer Rasch, Rafael Reisenhofer, Carola-Bibiane Schönlieb

专题命中 遥感融合与全色锐化 ：image fusion(title)；分类 cs.CV

Comments 24 pages, 18 figures, published in Inverse Problems, typo corrected, figure added

Journal ref Inverse Problems, 34(4), 044003, 2018

Deep Learning-Based Detail Map Estimation for MultiSpectral Image Fusion in Remote Sensing

Arian Azarang, Nasser Kehtarnavaz

专题命中 遥感融合与全色锐化 ：image fusion(title)；分类 eess.IV

Simulated JWST datasets for multispectral and hyperspectral image fusion

Claire Guilloteau, Thomas Oberlin, Olivier Berné, Nicolas Dobigeon

专题命中 遥感融合与全色锐化 ：image fusion(title)；分类 eess.IV

Multi-Resolution Multi-Modal Sensor Fusion For Remote Sensing Data With Label Uncertainty

Xiaoxiao Du, Alina Zare

专题命中 遥感融合与全色锐化 ：sensor fusion(title)；分类 cs.CV

Blind Hyperspectral-Multispectral Image Fusion via Graph Laplacian Regularization

Chandrajit Bajaj, Tianming Wang

专题命中 遥感融合与全色锐化 ：image fusion(title)；分类 cs.CV

Multispectral and Hyperspectral Image Fusion by MS/HS Fusion Net

Qi Xie, Minghao Zhou, Qian Zhao, Deyu Meng, Wangmeng Zuo, Zongben Xu

专题命中 遥感融合与全色锐化 ：image fusion(title)；分类 cs.CV

Comments 10 pages, 7 figures

Multispectral and Hyperspectral Image Fusion Using a 3-D-Convolutional Neural Network

Frosti Palsson, Johannes R. Sveinsson, Magnus O. Ulfarsson

专题命中 遥感融合与全色锐化 ：image fusion(title)；分类 cs.CV

FusionRF: High-Fidelity Satellite Neural Radiance Fields from Multispectral and Panchromatic Acquisitions

Michael Sprintson, Rama Chellappa, Cheng Peng

机构 * Johns Hopkins University（约翰霍普金斯大学） 纠错

专题命中 遥感融合与全色锐化 ：image fusion(abstract)；pansharpening(abstract)；分类 cs.CV、eess.IV

Guided Deep Decoder: Unsupervised Image Pair Fusion

Tatsumi Uezato, Danfeng Hong, Naoto Yokoya, Wei He

专题命中 遥感融合与全色锐化 ：image fusion(abstract)；pansharpening(abstract)；分类 cs.CV、eess.IV

Comments ECCV 2020

Classification of Hyperspectral and LiDAR Data Using Coupled CNNs

Renlong Hang, Zhu Li, Pedram Ghamisi, Danfeng Hong, Guiyu Xia, Qingshan Liu

专题命中 遥感融合与全色锐化 ：feature-level fusion(abstract)；decision-level fusion(abstract)；分类 cs.CV、eess.IV

Journal ref IEEE Transactions on Geoscience and Remote Sensing, 2020

MAG-Net: Physics-Aware Multi-Modal Fusion of Geostationary Satellite and Radar for Severe Convective Precipitation Nowcasting

MAG-Net：融合静止卫星和雷达的物理感知多模态融合用于强对流降水nowcasting

Dandan Chen, Yaqiang Wang, Anyuan Xiong, Enda Zhu

专题命中 遥感融合与全色锐化 ：multi-modal fusion(title)

AI总结 MAG-Net通过融合静止卫星和雷达数据，利用物理约束提升对强对流降水的nowcasting性能，优于现有确定性和生成性模型。

Physics and Human-Based Information Fusion for Improved Resident Space Object Tracking

Emmanuel Delande, Jeremie Houssineau, Moriba Jah

专题命中 遥感融合与全色锐化 ：information fusion(title)

Fusion and Grouping Strategies in Deep Learning for Local Climate Zone Classification of Multimodal Remote Sensing Data

深度学习中多模态遥感数据局部气候区分类的融合与分组策略

Ancymol Thomas, Jaya Sreevalsan-Nair

机构 * Graphics-Visualization-Computing Lab, International Institute of Information Technology Bangalore, Karnataka 560100, India（图形可视化计算实验室，国际信息学院班加罗尔，卡纳塔克邦560100，印度） 纠错

专题命中 遥感融合与全色锐化 ：decision-level fusion(abstract)；hybrid fusion(abstract)；分类 cs.CV

AI总结 本研究提出了一种基于深度学习的多模态遥感数据局部气候区分类方法，通过融合与分组策略提升分类准确率，最终达到76.6%的整体准确率。

Comments 25 pages, 12 figures

ReSPEC: A Framework for Online Multispectral Sensor Reconfiguration in Dynamic Environments

ReSPEC：动态环境中在线多光谱传感器重新配置框架

Yanchen Liu, Yuang Fan, Minghui Zhao, Xiaofan Jiang

机构 * Department of Electrical Engineering, Columbia University（电气工程系，哥伦比亚大学） 纠错

专题命中 遥感融合与全色锐化 ：sensor fusion(abstract)；multi-sensor fusion(abstract)；分类 cs.RO

AI总结 ReSPEC框架通过强化学习实现动态多光谱传感器重新配置，提升机器人在复杂环境下的感知效率与资源利用率。

Comments 8 pages, 4 figures. This work has been submitted to the IEEE for possible publication

Spatial-Spectral Binarized Neural Network for Panchromatic and Multi-spectral Images Fusion

Yizhen Jiang, Mengting Ma, Anqi Zhu, Xiaowen Ma, Jiaxin Li, Wei Zhang

机构 * Zhejiang University（浙江大学） ； Chongqing University of Posts and Telecommunications（重庆邮电大学） 纠错

专题命中 遥感融合与全色锐化 ：pansharpening(abstract)；pan-sharpening(abstract)；分类 cs.CV

PolSAM: Polarimetric Scattering Mechanism Informed Segment Anything Model

Yuqing Wang, Zhongling Huang, Shuxin Yang, Hao Tang, Xiaolan Qiu, Junwei Han, Dingwen Zhang

机构 * the BRain and Artificial INtelligence Lab (BRAIN LAB), School of Automation, Northwestern Polytechnical University（人工智能实验室（BRAIN LAB）、自动化学院、西北工业大学） ； the Shenzhen Research Institute of Northwestern Polytechnical University（西北工业大学深圳研究院） ； the National Key Laboratory for Multimedia Information Processing, School of Computer Science, Peking University（多媒体信息处理国家重点实验室、计算机科学学院、北京大学） ； the National Key Laboratory of Microwave Imaging Technology, Chinese Academy of Sciences（微波成像技术国家重点实验室、中国科学院） ； the Aerospace Information Research Institute, Chinese Academy of Sciences（航空信息研究所、中国科学院） 纠错

专题命中 遥感融合与全色锐化 ：multimodal fusion(abstract)；feature-level fusion(abstract)；分类 cs.CV

Comments The manuscript is 15 pages long, includes 13 figures and 5 tables

Sensor-Adaptive Flood Mapping with Pre-trained Multi-Modal Transformers across SAR and Multispectral Modalities

Tomohiro Tanaka, Narumasa Tsutsumida

机构 * Graduate school of Science & Engineering, Saitama University, Japan（埼玉大学理工学部） 纠错

专题命中 遥感融合与全色锐化 ：sensor fusion(abstract)；multi-sensor fusion(abstract)；分类 cs.CV

Comments 8 pages, 2 figures

Multimodal Transformer Using Cross-Channel attention for Object Detection in Remote Sensing Images

Bissmella Bahaduri, Zuheng Ming, Fangchen Feng, Anissa Mokraou

专题命中 遥感融合与全色锐化 ：multimodal fusion(abstract)；multi-modal fusion(abstract)；分类 cs.CV

Comments Accepted by ICIP2024

Guided Image Restoration via Simultaneous Feature and Image Guided Fusion

Xinyi Liu, Qian Zhao, Jie Liang, Hui Zeng, Deyu Meng, Lei Zhang

专题命中 遥感融合与全色锐化 ：pan-sharpening(abstract)；feature-level fusion(abstract)；分类 cs.CV

Recurrent Multiresolution Convolutional Networks for VHR Image Classification

John Ray Bergado, Claudio Persello, Alfred Stein

专题命中 遥感融合与全色锐化 ：image fusion(abstract)；pansharpening(abstract)；分类 cs.CV

MRFusion: A Deep Learning architecture to fuse PAN and MS imagery for land cover mapping

Raffaele Gaetano, Dino Ienco, Kenji Ose, Remi Cresson

专题命中 遥感融合与全色锐化 ：image fusion(abstract)；pansharpening(abstract)；分类 cs.CV

OceanBench: The Sea Surface Height Edition

J. Emmanuel Johnson, Quentin Febvre, Anastasia Gorbunova, Sammy Metref, Maxime Ballarotta, Julien Le Sommer, Ronan Fablet

专题命中 遥感融合与全色锐化 ：sensor fusion(abstract)；multi-sensor fusion(abstract)

Comments J. Emmanuel Johnson and Quentin Febvre contributed equally to this work

A 33-year NPP monitoring study in southwest China by the fusion of multi-source remote sensing and station data

Xiaobin Guan, Huanfeng Shen, Wenxia Gan, Gang Yang, Lunche Wang, Xinghua Li, Liangpei Zhang

专题命中 遥感融合与全色锐化 ：sensor fusion(abstract)；multi-sensor fusion(abstract)

Comments 20 pages, 11 figures

An iterative energy-based multimodal transformer for joint retrieval of wheat soil moisture, leaf area index, and plant height from Sentinel-1 and Sentinel-2 time series

基于迭代能量多模态Transformer的Sentinel-1与Sentinel-2时序联合反演小麦土壤水分、叶面积指数和株高

Shubham Kumar Singh, Peilei Fan, Suraj A. Yadav, Rajendra Prasad, Prashant K Srivastava

机构 * Department of Urban and Environmental Policy and Program, Tufts University（Tufts大学城市与环境政策与项目系） ； Electrical and Computer Engineering Department, Mississippi State University（密苏里州立大学电气与计算机工程系） ； Department of Physics, Indian Institute of Technology (BHU)（印度理工学院（BHU）物理系） ； Institute of Environment and Sustainable Development, Banaras Hindu University（巴纳尔斯赫尔大学环境与可持续发展研究所） 纠错

专题命中 遥感融合与全色锐化 ：multimodal fusion(abstract)；分类 cs.CV、eess.IV

AI总结 提出迭代能量Transformer（iEBT），通过嵌入多模态预测器并迭代更新目标向量，从Sentinel-1和Sentinel-2时序数据中联合反演土壤水分、叶面积指数和株高，在印度瓦拉纳西实测数据上取得高精度，并利用终端能量作为质量诊断指标。

Comparative analysis of dual-form networks for live land monitoring using multi-modal satellite image time series

多模态卫星图像时间序列用于实时土地监测的双形式网络比较分析

Iris Dumeur, Jérémy Anger, Gabriele Facciolo

机构 * 1 Kayrros SAS 2 Universit\'e Paris-Saclay, ENS Paris-Saclay, CNRS, Centre Borelli, 91190, Gif-sur-Yvette, France 3 Institut Universitaire de France 纠错

专题命中 遥感融合与全色锐化 ：sensor fusion(abstract)；分类 cs.CV、eess.IV

AI总结 本文研究了双形式注意力机制以提升多模态SITS分析效率，通过并行训练支持递归推理，针对时间不规则性和不一致性的挑战，提出基于实际获取日期计算token距离的方法，实验表明双形式机制在性能和效率上优于标准Transformer。

OSDM-MReg: Multimodal Image Registration based One Step Diffusion Model

OSDM-MReg: 基于一步扩散模型的多模态图像配准

Xiaochen Wei, Weiwei Guo, Wenxian Yu, Feiming Wei, Dongying Li

机构 * Shanghai Key Laboratory of Intelligent Sensing and Recognition（上海智能感知与识别重点实验室） ； Shanghai Jiao Tong University（上海交通大学） ； Center of Digital Innovation（数字创新中心） 纠错

专题命中 遥感融合与全色锐化 ：multimodal fusion(abstract)；分类 cs.CV、eess.IV

AI总结 OSDM-MReg通过一步扩散模型和多模态融合策略，实现多模态图像配准的高效准确配准。

DiffFuSR: Super-Resolution of all Sentinel-2 Multispectral Bands using Diffusion Models

DiffFuSR：利用扩散模型实现所有Sentinel-2多光谱波段的超分辨率处理

Muhammad Sarmad, Arnt-Børre Salberg, Michael Kampffmeyer

机构 * Norwegian Computing Center（挪威计算中心） ； Department of Physics and Technology, UiT The Arctic University of Norway（物理与技术系，UiT 北极大学） 纠错

专题命中 遥感融合与全色锐化 ：pansharpening(abstract)；分类 cs.CV、eess.IV

AI总结 DiffFuSR通过扩散模型和融合策略实现Sentinel-2多光谱波段的超分辨率处理，提升反射率保真度和光谱一致性。

Comments Accepted for Publication at IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (TGRS)

GDROS: A Geometry-Guided Dense Registration Framework for Optical-SAR Images under Large Geometric Transformations

Zixuan Sun, Shuaifeng Zhi, Ruize Li, Jingyuan Xia, Yongxiang Liu, Weidong Jiang

机构 * College of Electronic Science and Technology, National University of Defense Technology（电子科学与技术学院，国防科技大学） 纠错

专题命中 遥感融合与全色锐化 ：image fusion(abstract)；分类 cs.CV、eess.IV

Comments To be published in IEEE Transactions on Geoscience and Remote Sensing (T-GRS) 2025

Event-RGB Fusion for Spacecraft Pose Estimation Under Harsh Lighting

Mohsi Jawaid, Marcus Märtens, Tat-Jun Chin

机构 * AI for Space Group（空间人工智能小组） ； The University of Adelaide（阿德莱德大学） 纠错

专题命中 遥感融合与全色锐化 ：sensor fusion(abstract)；分类 cs.CV、cs.RO

Comments Associated dataset: https://zenodo.org/records/15861758

Journal ref Aerospace Science and Technology, Volume 168, Part E, January 2026, 111039

PAD: Phase-Amplitude Decoupling Fusion for Multi-Modal Land Cover Classification

Huiling Zheng, Xian Zhong, Bin Liu, Yi Xiao, Bihan Wen, Xiaofeng Li

机构 * Sanya Science and Education Innovation Park, Wuhan University of Technology, Sanya 572025, China（武汉理工大学三亚科学教育创新园） ； School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan 430070, China（武汉理工大学计算机科学与人工智能学院） ； Key Laboratory of Ocean Circulation and Waves, Institute of Oceanology, Chinese Academy of Sciences, Qingdao 266071, China（中国科学院海洋循环与波浪重点实验室） ； Hubei Key Laboratory of Transportation Internet of Things, School of Computer Science and Artificial Intelligence, Wuhan University of Technology, Wuhan 430070, China（湖北省交通物联网重点实验室） ； State Key Laboratory of Maritime Technology and Safety, Wuhan University of Technology, Wuhan 430063, China（武汉理工大学航海技术与安全国家重点实验室） ； College of Oceanography and Ecological Science, Shanghai Ocean University, Shanghai 201306, China（上海海洋大学海洋科学与生态学院） ； School of Computer and Artificial Intelligence, Zhengzhou University, Zhengzhou 450001, China（郑州大学计算机与人工智能学院） ； Rapid-Rich Object Search Lab, School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798（南洋理工大学电子与电气工程学院） 纠错

专题命中 遥感融合与全色锐化 ：multi-modal fusion(abstract)；分类 cs.CV、eess.IV

Comments 14 pages, 8 figures