A Spectral–Spatial Jointed Spectral Super-Resolution and Its Application to HJ-1A Satellite Images
نویسندگان
چکیده
To generate a high-spatial-resolution hyperspectral (HHS) image from multispectral (HMS) image, both spatial information and spectral should be considered simultaneously if we want to build more accurate mapping HMS HHS. this end, jointed super-resolution method is proposed in letter using an end-to-end learning strategy for each subspace with the cluster-based multibranch backpropagation neural network (BPNN). More specifically, addition spectra similarity, modified superpixel segmentation introduced jointly take contextual into account, new framework it given. Comparisons on Columbia University Automated Vision Environment (CAVE) data set show that our outperforms other relative state-of-the-art methods than 0.3 root mean squared error (RMSE) 1.0 angle mapper (SAM) index. Especially, exemplary application demonstrated synchronized observation collected by sensors mounted HJ-1A satellite at same time.
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ژورنال
عنوان ژورنال: IEEE Geoscience and Remote Sensing Letters
سال: 2022
ISSN: ['1558-0571', '1545-598X']
DOI: https://doi.org/10.1109/lgrs.2021.3073501