Advances and Challenges in Multimodal Remote Sensing Image Registration
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Abstract (arXiv)
Over the past few decades, with the rapid development of global aerospace and aerial remote sensing technology, the types of sensors have evolved from the traditional monomodal sensors (e.g., optical sensors) to the new generation of multimodal sensors [e.g., multispectral, hyperspectral, light detection and ranging (LiDAR) and synthetic aperture radar (SAR) sensors]. These advanced devices can dynamically provide various and abundant multimodal remote sensing images with different spatial, temporal, and spectral resolutions according to different application requirements. Since then, it is of great scientific significance to carry out the research of multimodal remote sensing image registration, which is a crucial step for integrating the complementary information among multimodal data and making comprehensive observations and analysis of the Earths surface. In this work, we will present our own contributions to the field of multimodal image registration, summarize the advantages and limitations of existing multimodal image registration methods, and then discuss the remaining challenges and make a forward-looking prospect for the future development of the field.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 12 of its 67 references that are in the map. First posted on arXiv 2 Feb 2023.
Builds on
12 of 67 references.
References · 12
- 2021LLVIP: A Visible-infrared Paired Dataset for Low-light Visioncited by 229
- 2019SEN12MS -- A Curated Dataset of Georeferenced Multi-Spectral Sentinel-1/2 Imagery for Deep Learning and Data Fusioncited by 95
- 2021DIML/CVL RGB-D Dataset: 2M RGB-D Images of Natural Indoor and Outdoor Scenescited by 45
- 2018The SEN1-2 Dataset for Deep Learning in SAR-Optical Data Fusioncited by 42
- 2021The QXS-SAROPT Dataset for Deep Learning in SAR-Optical Data Fusioncited by 27
- 2021Robust Registration of Multimodal Remote Sensing Images Based on Structural Similaritycited by 26
- 2018Identifying Corresponding Patches in SAR and Optical Images with a Pseudo-Siamese CNNcited by 18
- 2022A Robust Multimodal Remote Sensing Image Registration Method and System Using Steerable Filters with First- and Second-order Gradientscited by 10
- 2018The SARptical Dataset for Joint Analysis of SAR and Optical Image in Dense Urban Areacited by 8
- 2018Fast and Robust Matching for Multimodal Remote Sensing Image Registrationcited by 6
- 2020Improving Co-registration for Sentinel-1 SAR and Sentinel-2 Optical imagescited by 5
- 2020Fast and Robust Registration of Aerial Images and LiDAR data Based on Structrual Features and 3D Phase Correlationcited by 1
Built on by
Citing papers per year: 2024: 3; 2025: 3; 2026: 1.
7 papers.
- 2024Local Feature Matching Using Deep Learning: A Surveycited by 26
- 20243MOS: Multi-sources, Multi-resolutions, and Multi-scenes dataset for Optical-SAR image matchingcited by 8
- 2025Compress-Align-Detect: onboard change detection from unregistered imagescited by 1
- 2026Unregistered Spectral Image Fusion: Unmixing, Adversarial Learning, and Recoverabilitycited by 1
- 2024REMM:Rotation-Equivariant Framework for End-to-End Multimodal Image Matchingcited by 0
- 2025Grid-Reg: Detector-Free Gridized Feature Learning and Matching for Large-Scale SAR-Optical Image Registrationcited by 0
- 2025Coarse-to-Fine Non-Rigid Registration for Side-Scan Sonar Mosaickingcited by 0
- 2026Unregistered Spectral Image Fusion: Unmixing, Adversarial Learning, and Recoverability23 Mar 2026
- 2025Coarse-to-Fine Non-Rigid Registration for Side-Scan Sonar Mosaicking19 Nov 2025
- 2025Compress-Align-Detect: onboard change detection from unregistered images21 Jul 2025
- 2025Grid-Reg: Detector-Free Gridized Feature Learning and Matching for Large-Scale SAR-Optical Image Registration6 Jul 2025
- 2024REMM:Rotation-Equivariant Framework for End-to-End Multimodal Image Matching16 Jul 2024
- 20243MOS: Multi-sources, Multi-resolutions, and Multi-scenes dataset for Optical-SAR image matching1 Apr 2024
- 2024Local Feature Matching Using Deep Learning: A Survey31 Jan 2024