ECCV2020_CUCaNet:用于无监督超光谱超分辨率的耦合解混网络中的交叉注意,ECCV,2020年。(PyTorch)

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无监督的高光谱超分辨率耦合解混网中的交叉注意 ,, ,,和 论文代码:。 图。1。 受频谱分解技术启发的拟议的无监督超光谱超分辨率网络的图示,即具有交叉注意的耦合解混网(CUCaNet) ,该网络主要由两个重要模块组成:交叉注意和空间光谱一致性。 训练 请简单地运行./Main_CAVE.py演示,以在两个HSI(伪造的和真实的食物,图表和玩具)上重现我们的HSISR结果(将与在Windows OS上实现的Python 3.7使用)。 之前:有关必需的软件包,请参阅详细的.py文件。 参数:可以更好地调整权衡参数train_opt.lambda_* ,并且网络超参数灵活。 结果:请查看登录到./checkpoints/CAVE_*name*/precision.txt的五个评估指标(PSNR,SAM,ERGAS,SSIM和UIQI)以及保存在./Results/CAVE/的输出.m

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