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 (≥ …
Computational spectrometers enabled by nanophotonics and deep learning
A new type of spectrometer that heavily relies on computational technique to recover
spectral information is introduced. They are different from conventional optical spectrometers …
spectral information is introduced. They are different from conventional optical spectrometers …
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 …
Non-local meets global: An iterative paradigm for hyperspectral image restoration
Non-local low-rank tensor approximation has been developed as a state-of-the-art method
for hyperspectral image (HSI) restoration, which includes the tasks of denoising …
for hyperspectral image (HSI) restoration, which includes the tasks of denoising …
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 …
End-to-end low cost compressive spectral imaging with spatial-spectral self-attention
Coded aperture snapshot spectral imaging (CASSI) is an effective tool to capture real-world
3D hyperspectral images. While a number of existing work has been conducted for …
3D hyperspectral images. While a number of existing work has been conducted for …
Deep gaussian scale mixture prior for spectral compressive imaging
In coded aperture snapshot spectral imaging (CASSI) system, the real-world hyperspectral
image (HSI) can be reconstructed from the captured compressive image in a snapshot …
image (HSI) can be reconstructed from the captured compressive image in a snapshot …
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 …