RAFNet uses wavelet-based directional separation, K-means regional clustering, and clustered sparse attention to create adaptive kernels and efficient frequency aggregation, outperforming prior pansharpening networks on benchmark datasets.
Panchromatic and multispectral image fusion for remote sensing and earth observation: Concepts, taxonomy, literature review, evaluation methodologies and challenges ahead
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
RAFNet: Region-Aware Fusion Network for Pansharpening
RAFNet uses wavelet-based directional separation, K-means regional clustering, and clustered sparse attention to create adaptive kernels and efficient frequency aggregation, outperforming prior pansharpening networks on benchmark datasets.