7 citations · 12 across the 4 of their papers we have counts for
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cs.CV2023★ 2 cited
Spectral Enhanced Rectangle Transformer for Hyperspectral Image Denoising
Miaoyu Li, Ji Liu, Ying Fu +2
Denoising is a crucial step for hyperspectral image (HSI) applications. Though witnessing the great power of deep learning, existing HSI denoising methods suffer from limitations i…
cs.CV2023★ 3 cited
LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoising
Zichun Wang, Ying Fu, Ji Liu +1
Despite the significant results on synthetic noise under simplified assumptions, most self-supervised denoising methods fail under real noise due to the strong spatial noise correl…
cs.CV2023★ 7 cited
Mixed Attention Network for Hyperspectral Image Denoising
Zeqiang Lai, Ying Fu
Hyperspectral image denoising is unique for the highly similar and correlated spectral information that should be properly considered. However, existing methods show limitations in…