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 (≥ …

Snapshot compressive imaging (SCI) aims to capture the high-dimensional (usually 3D)
images using a 2D sensor (detector) in a single snapshot. Though enjoying the advantages …

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 …

We propose the l-net, which reconstructs hyperspectral images (eg, with 24 spectral
channels) from a single shot measurement. This task is usually termed snapshot …

A blind compressive sensing algorithm is proposed to reconstruct hyperspectral images from
spectrally-compressed measurements. The wavelength-dependent data are coded and then …

Real-world data processing problems often involve various image modalities associated
with a certain scene, including RGB images, infrared images, or multispectral images. The …

Coded aperture compressive spectral imagers (CSI) sense a three-dimensional data cube
by using two-dimensional projections of the coded and spectrally dispersed input image …

In support of art investigation, we propose a new source separation method that unmixes a
single X-ray scan acquired from double-sided paintings. In this problem, the X-ray signals to …

Approximate message passing (AMP) methods have gained recent traction in sparse signal
recovery. Additional information about the signal, or side information (SI), is commonly …

Hyperspectral imaging (HSI) has been widely investigated within the context of
computational imaging due to the high dimensional challenges for direct imaging. However …