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 (≥ …
A systematic review of compressive sensing: Concepts, implementations and applications
M Rani, SB Dhok, RB Deshmukh - IEEE access, 2018 - ieeexplore.ieee.org
Compressive Sensing (CS) is a new sensing modality, which compresses the signal being
acquired at the time of sensing. Signals can have sparse or compressible representation …
acquired at the time of sensing. Signals can have sparse or compressible representation …
[PDF][PDF] 压缩感知理论及其研究进展
石光明， 刘丹华， 高大化， 刘哲， 林杰， 王良君 - 电子学报, 2009 - ejournal.org.cn
信号采样是联系模拟信源和数字信息的桥梁. 人们对信息的巨量需求造成了信号采样,
传输和存储的巨大压力. 如何缓解这种压力又能有效提取承载在信号中的有用信息是信号与信息 …
传输和存储的巨大压力. 如何缓解这种压力又能有效提取承载在信号中的有用信息是信号与信息 …
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 …
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 …
Optimization methods for large-scale machine learning
This paper provides a review and commentary on the past, present, and future of numerical
optimization algorithms in the context of machine learning applications. Through case …
optimization algorithms in the context of machine learning applications. Through case …
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 …