Computational spectral imaging: a contemporary overview
Spectral imaging collects and processes information along spatial and spectral coordinates
quantified in discrete voxels, which can be treated as a 3D spectral data cube. The spectral …
quantified in discrete voxels, which can be treated as a 3D spectral data cube. The spectral …
Compressive spectral image reconstruction using deep prior and low-rank tensor representation
J Bacca, Y Fonseca, H Arguello - Applied optics, 2021 - opg.optica.org
Compressive spectral imaging (CSI) has emerged as an alternative spectral image
acquisition technology, which reduces the number of measurements at the cost of requiring …
acquisition technology, which reduces the number of measurements at the cost of requiring …
Deep-learning supervised snapshot compressive imaging enabled by an end-to-end adaptive neural network
Snapshot compressive imaging (SCI) is an advanced approach for single-shot high-
dimensional data visualization. Deep learning is popularly used to improve SCI's …
dimensional data visualization. Deep learning is popularly used to improve SCI's …
Practical snapshot hyperspectral imaging with DOE
H Hu, H Zhou, Z Xu, Q Li, H Feng, Y Chen… - Optics and Lasers in …, 2022 - Elsevier
As the pursuit of snapshot spectral imaging continued to grow, traditional hyperspectral
imaging systems have been too enormous and too slow to implement in real scenarios …
imaging systems have been too enormous and too slow to implement in real scenarios …
[HTML][HTML] Deep‐learning based on‐chip rapid spectral imaging with high spatial resolution
Spectral imaging extends the concept of traditional color cameras to capture images across
multiple spectral channels and has broad application prospects. Conventional spectral …
multiple spectral channels and has broad application prospects. Conventional spectral …
Efficient physics-based learned reconstruction methods for real-time 3D near-field MIMO radar imaging
Near-field multiple-input multiple-output (MIMO) radar imaging systems have recently
gained significant attention. These systems generally reconstruct the three-dimensional (3D) …
gained significant attention. These systems generally reconstruct the three-dimensional (3D) …
High accurate and efficient 3D network for image reconstruction of diffractive-based computational spectral imaging
H Fan, C Li, H Xu, L Zhao, X Zhang, H Jiang… - IEEE Access, 2024 - ieeexplore.ieee.org
Diffractive optical imaging spectroscopy as a promising miniaturized and high throughput
portable spectral imaging technique suffers from the problem of low precision and slow …
portable spectral imaging technique suffers from the problem of low precision and slow …
Momentum accelerated unfolding network with spectral–spatial prior for computational spectral imaging
Edge computing is a key technology in computational imaging, where the algorithms
determine reconstruction quality and reconstruction speed. Recovering spectral information …
determine reconstruction quality and reconstruction speed. Recovering spectral information …
Optical information processing: A historical overview
HM Ozaktas, MA Kutay - Digital Signal Processing, 2021 - Elsevier
Optical information processing lies at the intersection of optics and signal processing. It
involves the processing of optical information as well as the use of optical means to process …
involves the processing of optical information as well as the use of optical means to process …
计算光谱成像: 光场编码与算法解码(特邀)
郭家骐， 范本轩， 刘鑫， 刘雨慧， 王绪泉… - Laser & …, 2024 - opticsjournal.net
摘要光谱成像旨在获取目标场景空间-光谱三维数据立方体, 从而显著提高对目标的识别和分类
能力, 广泛应用于** 和民用等多个领域. 传统光谱成像技术多基于奈奎斯特采样理论构建 …
能力, 广泛应用于** 和民用等多个领域. 传统光谱成像技术多基于奈奎斯特采样理论构建 …