SSPSR:用于单个高光谱图像超分辨率(IEEE TCI)的空间光谱先验深度网络-源码

上传者: 42134143 | 上传时间: 2021-06-19 15:58:08 | 文件大小: 2.97MB | 文件类型: ZIP
SSPSR-Pytorch 论文: : (IEEE Xplore) (arXiv) 学习空间光谱先验以实现超光谱影像的超分辨率 在本文中,我们引入了空间光谱先验网络(SSPN),以充分利用空间信息和高光谱数据的光谱之间的相关性。 考虑到高光谱训练样本稀少且高光谱图像数据的光谱维数很高,因此训练稳定有效的深度网络并非易事。 因此,提出了一种组卷积(具有共享的网络参数)和渐进式上采样框架。 这不仅减轻了由于高光谱数据的高维而导致的特征提取的困难,而且使训练过程更加稳定。 为了利用空间和光谱先验,我们设计了一个空间光谱块(SSB),它由一个空间残差模块和一个光谱注意残差模块组成。 网络架构 拟议的SSPSR网络的整体网络架构 空间光谱块(SSB)的网络架构 结果 筑西数据集 Chikusei数据集上不同方法的平均定量比较。 帕维亚数据集 Pavia Center数据集上不同方法的平均

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