Multimodal Remote Sensing Image Registration: A Comprehensive Review, Challenges and Prospects

arXiv:2610.11176 · cs.CV · Submitted 2026-10-08 · Read on arXiv

cs.CV

Submitted: 2026-10-08

Updated: 2026-10-08

Terminology

• Transformer — 18× in this paper · explained in 2 episodes
• Accuracy — 17× in this paper · explained in 1 episode
• Robustness — 16× in this paper · explained in 5 episodes
• Core — 14× in this paper · explained in 2 episodes
• Consistency — 13× in this paper · explained in 3 episodes
• Feature Extraction — 12× in this paper · explained in 2 episodes
• Phase Congruency — 12× in this paper
• Alignment — 10× in this paper · explained in 1 episode
• Attention Mechanism — 8× in this paper · explained in 3 episodes
• Generalization — 6× in this paper · explained in 13 episodes
• Loss Function — 5× in this paper · explained in 2 episodes
• Benchmark — 4× in this paper · explained in 2 episodes
• Transformer Architecture — 4× in this paper · explained in 2 episodes
• Aggregation — 3× in this paper · explained in 1 episode
• Generalizability — 3× in this paper · explained in 6 episodes
• Adaptation — 2× in this paper · explained in 1 episode
• Computational overhead — 2× in this paper · explained in 2 episodes
• Data Fusion — 2× in this paper · explained in 3 episodes
• Detail Enhancement Module — 2× in this paper
• Diffusion Model — 2× in this paper · explained in 8 episodes
• Generative Adversarial Networks (GANs) — 2× in this paper · explained in 3 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Histogram of Oriented Phase Congruency — 2× in this paper
• Interpretability — 2× in this paper · explained in 15 episodes
• Maximum Index Map — 2× in this paper
• Rational Polynomial Coefficient — 2× in this paper
• Segment Anything Model — 2× in this paper
• Abstraction — 1× in this paper · explained in 1 episode
• Adaptability — 1× in this paper · explained in 1 episode
• Adversarial Model — 1× in this paper · explained in 1 episode
• Convolutional Neural Networks (CNNs) — 1× in this paper · explained in 2 episodes
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Dense Local Self-Similarity — 1× in this paper
• Feature Selection — 1× in this paper · explained in 4 episodes
• Generative Models — 1× in this paper · explained in 3 episodes
• Histogram of Absolute Phase Congruency Gradients — 1× in this paper
• Histogram of Oriented Gradients — 1× in this paper
• Hybrid Model — 1× in this paper · explained in 2 episodes
• Local Histogram of Oriented Phase Congruency — 1× in this paper
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Normalized Cross-Correlation — 1× in this paper
• Optical Flow — 1× in this paper · explained in 2 episodes
• Physical Constraints — 1× in this paper · explained in 7 episodes
• Point Clouds — 1× in this paper · explained in 2 episodes
• Position and Orientation System — 1× in this paper
• Quantization — 1× in this paper · explained in 12 episodes
• Radiation-variation Insensitive Feature Transform — 1× in this paper
• Rotation-invariant Maximum Index Map — 1× in this paper
• Segment Anything Model (SAM) — 1× in this paper · explained in 2 episodes
• Sparsity — 1× in this paper · explained in 4 episodes
• Spatial Pyramid Aggregated Pooling — 1× in this paper
• Speeded-Up Robust Features — 1× in this paper
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• The QXS-SAROPT Dataset for Deep Learning in SAR-Optical Data Fusion
• RIFT2: Speeding-up RIFT with A New Rotation-Invariance Technique
• Attention Is All You Need
• Hyperspectral and multispectral image fusion with arbitrary resolution through self-supervised representations
• OSDM-MReg: Multimodal Image Registration based One Step Diffusion Model

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