Spectral variations pose a common challenge in analyzing hyperspectral images (HSI). To address this, low-rank tensor representation has emerged as a robust strategy, leveraging inherent correlations ...

In order to improve the fusion of infrared and visible images, a novel and effective fusion method is proposed based on multi-scale transform and sparse low-rank representation in this paper. Visible ...

Hyperspectral image classification is an attractive and challenging task due to the difficulty to acquire large labeled datasets, and its susceptibility to natural environmental influences. Deep ...