Volumetric emission tomography for combustion processes
This is a comprehensive, critical, and pedagogical review of volumetric emission
tomography for combustion processes. Many flames that are of interest to scientists and …
tomography for combustion processes. Many flames that are of interest to scientists and …
Deep learning meets hyperspectral image analysis: A multidisciplinary review
Modern hyperspectral imaging systems produce huge datasets potentially conveying a great
abundance of information; such a resource, however, poses many challenges in the …
abundance of information; such a resource, however, poses many challenges in the …
Mst++: Multi-stage spectral-wise transformer for efficient spectral reconstruction
Existing leading methods for spectral reconstruction (SR) focus on designing deeper or
wider convolutional neural networks (CNNs) to learn the end-to-end map** from the RGB …
wider convolutional neural networks (CNNs) to learn the end-to-end map** from the RGB …
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 …
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 …
Rank minimization for snapshot compressive imaging
Snapshot compressive imaging (SCI) refers to compressive imaging systems where multiple
frames are mapped into a single measurement, with video compressive imaging and …
frames are mapped into a single measurement, with video compressive imaging and …
Plug-and-play algorithms for large-scale snapshot compressive imaging
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 …
images using a 2D sensor (detector) in a single snapshot. Though enjoying the advantages …
l-net: Reconstruct hyperspectral images from a snapshot measurement
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 …
channels) from a single shot measurement. This task is usually termed snapshot …
Deeply learned broadband encoding stochastic hyperspectral imaging
Many applications requiring both spectral and spatial information at high resolution benefit
from spectral imaging. Although different technical methods have been developed and …
from spectral imaging. Although different technical methods have been developed and …