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Modular gradient-saliency parallel attention and efficient multi-scale shuffle for ISAR-optical image fusion
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DOI：10.1016/j.patcog.2026.113881.png)
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Abstract
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• Inspired by high-pass filtering, a novel modular GSPA fusion strategy is proposed. • MS 2M efficiently captures and aggregates multi-scale features for better fusion. • A novel GRMS 2Net pioneers deep learning for ISAR and optical image fusion.
Keywords:
GSPA fusion
multi-scale features
ISAR-optical image fusion
deep learning
gradient-saliency attention