3 papers
cs.CV2023
Hyperspectral Target Detection Based on Low-Rank Background Subspace Learning and Graph Laplacian Regularization
Dunbin Shen, Xiaorui Ma, Wenfeng Kong +2
Hyperspectral target detection is good at finding dim and small objects based on spectral characteristics. However, existing representation-based methods are hindered by the proble…
eess.IV2021
Multi-modal and frequency-weighted tensor nuclear norm for hyperspectral image denoising
Xiaozhen Xie, Sheng Liu
Low-rankness is important in the hyperspectral image (HSI) denoising tasks. The tensor nuclear norm (TNN), defined based on the tensor singular value decomposition, is a state-of-t…
cs.CV2021
Hyperspectral Image Denoising via Multi-modal and Double-weighted Tensor Nuclear Norm
Sheng Liu, Xiaozhen Xie, Wenfeng Kong
Hyperspectral images (HSIs) usually suffer from different types of pollution. This severely reduces the quality of HSIs and limits the accuracy of subsequent processing tasks. HSI…