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Found 5 papers, 0 papers with code
Proximal PanNet: A Model-Based Deep Network for Pansharpening
To alleviate this issue, we propose a novel deep network for pansharpening by combining the model-based methodology with the deep learning method.
Super-resolution reconstruction of hyperspectral images via low rank tensor modeling and total variation regularization
In this paper, we propose a novel approach to hyperspectral image super-resolution by modeling the global spatial-and-spectral correlation and local smoothness properties over hyperspectral images.
A Novel Sparsity Measure for Tensor Recovery
In this paper, we propose a new sparsity regularizer for measuring the low-rank structure underneath a tensor.
Total Variation Regularized Tensor RPCA for Background Subtraction from Compressive Measurements
In this paper, we propose a novel tensor-based robust PCA (TenRPCA) approach for BSCM by decomposing video frames into backgrounds with spatial-temporal correlations and foregrounds with spatio-temporal continuity in a tensor framework.
Learning a Convolutional Neural Network for Non-uniform Motion Blur Removal
In this paper, we address the problem of estimating and removing non-uniform motion blur from a single blurry image.
