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Neural Shrödinger bridge matching for pansharpening
Inverse Problems and ImagingRecent diffusion probabilistic models (DPMs) in the field of pansharpening have gradually gained attention and achieved state-of-the-art (SOT A) performance. In this paper, we identify shortcomings in directly applying DPMs to the task of pansharpening as an inverse problem, including 1) initiating sampling directly from Gaussian noise neglects the low-
Cao, Zi-Han +3 more
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Machine Learning in Pansharpening: A benchmark, from shallow to deep networks
IEEE Geoscience and Remote Sensing Magazine, 2022Giuseppe Scarpa +2 more
exaly
Atmospheric corrections for pansharpening
2017Among remote sensing image fusion applications, panchromatic (Pan) sharpening, or pansharpening, of a multispectral (MS) image has received considerable attention over the last quarter of century. Pansharpening techniques take advantage of the complementary characteristics of spatial and spectral resolutions of MS and Pan data, in order to synthesize a
Luciano Alparone +3 more
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CTCP: Cross Transformer and CNN for Pansharpening
Proceedings of the 31st ACM International Conference on Multimedia, 2023Zhao Su +6 more
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Improved Generalized IHS Based on Total Variation for Pansharpening
Remote Sensing, 2023Xiaobing Dai +2 more
exaly
Supervised-unsupervised combined deep convolutional neural networks for high-fidelity pansharpening
Information Fusion, 2023Shutao Li, Feng Shao, Xiangchao Meng
exaly
Multipatch Progressive Pansharpening With Knowledge Distillation
IEEE Transactions on Geoscience and Remote Sensing, 2023Meiqi Gong +4 more
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A continual learning-guided training framework for pansharpening
ISPRS Journal of Photogrammetry and Remote Sensing, 2023Simone Lolli, Gemine Vivone, Xue Yang
exaly
A differential information residual convolutional neural network for pansharpening
ISPRS Journal of Photogrammetry and Remote Sensing, 2020Liangpei Zhang, Qiangqiang Yuan
exaly