Snapshot compressive imaging: Theory, algorithms, and applications
Capturing high-dimensional (HD) data is a long-term challenge in signal processing and
related fields. Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥ …
related fields. Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥ …
Mask-guided spectral-wise transformer for efficient hyperspectral image reconstruction
Hyperspectral image (HSI) reconstruction aims to recover the 3D spatial-spectral signal from
a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system. The …
a 2D measurement in the coded aperture snapshot spectral imaging (CASSI) system. The …
Hdnet: High-resolution dual-domain learning for spectral compressive imaging
The rapid development of deep learning provides a better solution for the end-to-end
reconstruction of hyperspectral image (HSI). However, existing learning-based methods …
reconstruction of hyperspectral image (HSI). However, existing learning-based methods …
Degradation-aware unfolding half-shuffle transformer for spectral compressive imaging
In coded aperture snapshot spectral compressive imaging (CASSI) systems, hyperspectral
image (HSI) reconstruction methods are employed to recover the spatial-spectral signal from …
image (HSI) reconstruction methods are employed to recover the spatial-spectral signal from …
Coarse-to-fine sparse transformer for hyperspectral image reconstruction
Many learning-based algorithms have been developed to solve the inverse problem of
coded aperture snapshot spectral imaging (CASSI). However, CNN-based methods show …
coded aperture snapshot spectral imaging (CASSI). However, CNN-based methods show …
Pixel adaptive deep unfolding transformer for hyperspectral image reconstruction
Hyperspectral Image (HSI) reconstruction has made gratifying progress with the deep
unfolding framework by formulating the problem into a data module and a prior module …
unfolding framework by formulating the problem into a data module and a prior module …
Self-supervised neural networks for spectral snapshot compressive imaging
We consider using untrained neural networks to solve the reconstruction problem of
snapshot compressive imaging (SCI), which uses a two-dimensional (2D) detector to …
snapshot compressive imaging (SCI), which uses a two-dimensional (2D) detector to …
Fusformer: A transformer-based fusion network for hyperspectral image super-resolution
Hyperspectral image super-resolution (HISR) is to fuse a low-resolution hyperspectral image
(LR-HSI) and a high-resolution multispectral image (HR-MSI), aiming to obtain a high …
(LR-HSI) and a high-resolution multispectral image (HR-MSI), aiming to obtain a high …