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Optical and SAR Image Fusion: A Review of Theories, Methods, and Applications
by
Li, Peixuan
, Wang, Haipeng
, Li, Zhuoxuan
, Zhang, Ruyi
, Yang, Yi
in
Artificial satellites in remote sensing
/ Complementarity
/ Computer vision
/ Data integration
/ Deep learning
/ Dielectric properties
/ fusion methods
/ image fusion
/ Open data
/ optical imagery
/ Radar imaging
/ Radiation
/ Remote sensing
/ Remote sensing systems
/ SAR imagery
/ Sensors
/ Synthetic aperture radar
/ Vegetation
2026
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Optical and SAR Image Fusion: A Review of Theories, Methods, and Applications
by
Li, Peixuan
, Wang, Haipeng
, Li, Zhuoxuan
, Zhang, Ruyi
, Yang, Yi
in
Artificial satellites in remote sensing
/ Complementarity
/ Computer vision
/ Data integration
/ Deep learning
/ Dielectric properties
/ fusion methods
/ image fusion
/ Open data
/ optical imagery
/ Radar imaging
/ Radiation
/ Remote sensing
/ Remote sensing systems
/ SAR imagery
/ Sensors
/ Synthetic aperture radar
/ Vegetation
2026
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Do you wish to request the book?
Optical and SAR Image Fusion: A Review of Theories, Methods, and Applications
by
Li, Peixuan
, Wang, Haipeng
, Li, Zhuoxuan
, Zhang, Ruyi
, Yang, Yi
in
Artificial satellites in remote sensing
/ Complementarity
/ Computer vision
/ Data integration
/ Deep learning
/ Dielectric properties
/ fusion methods
/ image fusion
/ Open data
/ optical imagery
/ Radar imaging
/ Radiation
/ Remote sensing
/ Remote sensing systems
/ SAR imagery
/ Sensors
/ Synthetic aperture radar
/ Vegetation
2026
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Optical and SAR Image Fusion: A Review of Theories, Methods, and Applications
Journal Article
Optical and SAR Image Fusion: A Review of Theories, Methods, and Applications
2026
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Overview
Remote sensing technology has become an indispensable core means for Earth observation. As two of the most commonly used remote sensing modalities, the fusion of optical and synthetic aperture radar (SAR) (OPT-SAR fusion) can effectively overcome the limitations of a single data source, achieve information complementarity and synergistic enhancement, thereby significantly improving the interpretation capability of multi-source remote sensing data. This paper first discusses the necessity of OPT-SAR fusion, systematically reviews the historical development of fusion technologies, and summarizes open-source resources for various tasks, aiming to provide a reference for related research. Finally, building upon recent advances in OPT-SAR fusion research and cutting-edge developments in deep learning, this paper proposes that future fusion technologies should develop in the following directions: interpretable fusion models driven by both data and knowledge, general fusion perception driven by multimodal large models, and lightweight architectures with efficient deployment strategies.
Publisher
MDPI AG
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