Optical and SAR Image Fusion: A Review of Theories, Methods, and Applications

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.

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Publication Details

Journal
Remote Sensing
Published
2025-12-25
DOI
https://doi.org/10.3390/rs18010073
Citations
2
Primary Topic
Advanced Image Fusion Techniques
Type
article
Field-Weighted Citation Impact
2.27

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article

Optical and SAR Image Fusion: A Review of Theories, Methods, and Applications

Hao Wang, Pengfei Li, Ruyi Zhang, Zhuoxuan Li et al.
2 citations
Remote Sensing
Advanced Image Fusion Techniques
2.27
article

Optical and SAR Image Fusion: A Review of Theories, Methods, and Applications

Hao Wang, Pengfei Li, Ruyi Zhang, Zhuoxuan Li, Yi Yang
article en
2 citations

Abstract

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.

Remote SensingVol. 18(1)
Fudan University (CN)
National Natural Science Foundation of China
Industry, innovation and infrastructure
Openalex Percentile: Top 9%
Advanced Image Fusion Techniques
2.27
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