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home/Knowledge Base/CODES/Hyperspectral/Spectral Superresolution of Multispectral Imagery With Joint Sparse and Low-Rank Learning

Spectral Superresolution of Multispectral Imagery With Joint Sparse and Low-Rank Learning

June 29, 2020

Spectral Superresolution of Multispectral Imagery With Joint Sparse and Low-Rank Learning
L. Gao, D. Hong, J. Yao, B. Zhang, P. Gamba and J. Chanussot

Geoscience and Remote Sensing, IEEE Transactions on
DOI: 10.1109/TGRS.2020.3000684

code : https://github.com/danfenghong/IEEE_TGRS_J-SLoL

Tags:dictionary learninghyperspectraljoint learninglow-rankMultispectralremote sensingsparse representationsuperresolution
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Categories
  • CODES
    • Anomaly
    • Change Detection
    • Classification of Hyperspectral Images
    • Classification of Remote Sensing Data
    • Data fusion: hyperspectral + Lidar
    • Data fusion: Hyperspectral + Multispectral
    • Deep Learning
    • Denoising
    • Feature Extraction
    • Graphs
    • Graphs, Manifold
    • Hyperspectral
    • Hyperspectral remote sensing
    • Hyperspectral Super Resolution
    • Infrared
    • Machine Learning in Remote Sensing
    • Multi-modal
    • Object Detection
    • Pansharpening
    • Registration
    • Sequences
    • Spectral Unmixing
    • Super Resolution
    • Synthetic Aperture Radar and Radar Sounder
    • Target Detection
    • Tensor
    • Transformer
  • DATA

  Spectralformer: Rethinking hyperspectral image classification with transformers

Sparsity-Enhanced Convolutional Decomposition: A Novel Tensor-Based Paradigm for Blind Hyperspectral Unmixing  

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Mail : Jocelyn Chanussot

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http://www.jocelyn-chanussot.net

 

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