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Found 4 papers, 2 papers with code
TDiffDe: A Truncated Diffusion Model for Remote Sensing Hyperspectral Image Denoising
Hyperspectral images play a crucial role in precision agriculture, environmental monitoring or ecological analysis.
EDiffSR: An Efficient Diffusion Probabilistic Model for Remote Sensing Image Super-Resolution
Recently, convolutional networks have achieved remarkable development in remote sensing image Super-Resoltuion (SR) by minimizing the regression objectives, e. g., MSE loss.
Local-Global Temporal Difference Learning for Satellite Video Super-Resolution
To explore the global dependency in the entire frame sequence, a Long-term Temporal Difference Module (L-TDM) is proposed, where the differences between forward and backward segments are incorporated and activated to guide the modulation of the temporal feature, leading to a holistic global compensation.
Spectral Response Function Guided Deep Optimization-driven Network for Spectral Super-resolution
Hyperspectral images are crucial for many research works.
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