Coded aperture imaging (CAI) is a technique to image three-dimensional scenes with
special controlled abilities. In this review, we survey several recently proposed techniques to …

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 coupled deep learning approach for coded aperture design and single-pixel
measurements classification is proposed. A whole neural network is trained to …

With the development of computer science, more and more hardware implementations can
be reproduced by software programming, bringing compact, cheap, and fast components to …

摘要早期压缩感知在光学成像领域的应用主要集中在空域压缩成像. 近年来,
更多的空域压缩成像采用阵列式探测器取代单元探测器采集测量值. 同时 …

Recently, many deep neural networks (DNN) have been proposed to solve the spectral
reconstruction (SR) problem: recovering spectra from RGB measurements. Most DNNs seek …

Spectral reconstruction algorithms recover spectra from RGB sensor responses. Recent
methods—with the very best algorithms using deep learning—can already solve this …

Spectral reconstruction (SR) algorithms attempt to recover hyperspectral information from
RGB camera responses. Recently, the most common metric for evaluating the performance …

Light detection and ranging (Lidar) single-photon devices capture range and intensity
information from a three-dimensional (3-D) scene. This modality enables long range 3-D …

Hyperspectral imaging is being extensively investigated owing to its promising future in
critical applications such as medical diagnostics, sensing, and surveillance. However …