A dual-prior attention module adds semantic homogeneity and geometric boundary constraints to low-light remote sensing enhancement and outperforms prior methods on most tested benchmarks.
Spatial–frequency dual-domain feature fusion network for low-light remote sensing image enhancement,
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Overcoming Attention Drift: Homogeneity-Heterogeneity Guided Feature Aggregation for Low-Light Remote Sensing Image Enhancement
A dual-prior attention module adds semantic homogeneity and geometric boundary constraints to low-light remote sensing enhancement and outperforms prior methods on most tested benchmarks.