Feb 25, 2021 · This article reviews recent advances in SCI hardware, theory, and algorithms, including both optimizationbased and deep learning-based algorithms.
Mar 7, 2021 · This paper develops a memory-efficient network for large-scale video SCI based on multi-group reversible 3D convolutional neural networks.
Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥3D) data in a snapshot measurement. Via novel optical designs, the 2D detector samples the ...
Snapshot compressive imaging (SCI) uses a 2D detector to capture HD (≥3D) data in a snapshot measurement. Via novel optical designs, the 2D detector samples the ...
Recent advances in SCI hardware, theory, and algorithms are reviewed, including both optimizationbased and deep learning-based algorithms.
Jun 6, 2024 · In this paper, we focus on SCI recovery algorithms that employ untrained neural networks (UNNs), such as deep image prior (DIP), to model source structure.
Jul 15, 2019 · Snapshot compressive imaging (SCI) refers to compressive imaging systems where multiple frames are mapped into a single measurement, which has ...
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Mar 9, 2021 · This article reviews recent advances in SCI hardware, theory and algorithms, including both optimization-based and deep-learning-based ...
In this article, we use SCI for 3D signals to demonstrate ideas, theory, and algorithms, with video SCI and spectral SCI as two representative applications. The ...
Snapshot Compressive Imaging: Theory, Algorithms, and Applications
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