The authors propose JLRST, a subspace-based unified tensor regularizer that jointly enforces low-rankness and local smoothness on gradient tensors of clustered coefficients, solved via ADMM with mode-3 logarithmic TNN.
Hyperspectral image super- resolution via adaptive factor group sparsity regularization-based sub- space representation
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Low-rankness and Smoothness Meet Subspace: A Unified Tensor Regularization for Hyperspectral Image Super-resolution
The authors propose JLRST, a subspace-based unified tensor regularizer that jointly enforces low-rankness and local smoothness on gradient tensors of clustered coefficients, solved via ADMM with mode-3 logarithmic TNN.