mlsanityData to 7 Oct 2026

Compressive Hyperspectral Imaging with Side Information

arXiv 1502.06260 ↗First posted 22 Feb 2015cs.CVcited by 19

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Abstract (arXiv)

A blind compressive sensing algorithm is proposed to reconstruct hyperspectral images from spectrally-compressed measurements.The wavelength-dependent data are coded and then superposed, mapping the three-dimensional hyperspectral datacube to a two-dimensional image. The inversion algorithm learns a dictionary em in situ from the measurements via global-local shrinkage priors. By using RGB images as side information of the compressive sensing system, the proposed approach is extended to learn a coupled dictionary from the joint dataset of the compressed measurements and the corresponding RGB images, to improve reconstruction quality. A prototype camera is built using a liquid-crystal-on-silicon modulator. Experimental reconstructions of hyperspectral datacubes from both simulated and real compressed measurements demonstrate the efficacy of the proposed inversion algorithm, the feasibility of the camera and the benefit of side information.

Key facts. Cited by 19 papers in the map (data through 7 Oct 2026). First posted on arXiv 22 Feb 2015.

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Citing papers per year: 2021: 10; 2022: 3; 2023: 4; 2024: 2.

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  1. 2021Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstructioncited by 110
  2. 2022Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imagingcited by 66
  3. 2021Deep Gaussian Scale Mixture Prior for Spectral Compressive Imagingcited by 58
  4. 2021Plug-and-Play Algorithms for Video Snapshot Compressive Imagingcited by 42
  5. 2021Self-supervised Neural Networks for Spectral Snapshot Compressive Imagingcited by 35
  6. 2021Memory-Efficient Network for Large-scale Video Compressive Sensingcited by 30
  7. 2021MetaSCI: Scalable and Adaptive Reconstruction for Video Compressive Sensingcited by 29
  8. 2023Binarized Spectral Compressive Imagingcited by 23
  9. 2022Spatial-Temporal Transformer for Video Snapshot Compressive Imagingcited by 21
  10. 2023EfficientSCI: Densely Connected Network with Space-time Factorization for Large-scale Video Snapshot Compressive Imagingcited by 18
  11. 2023In2SET: Intra-Inter Similarity Exploiting Transformer for Dual-Camera Compressive Hyperspectral Imagingcited by 8
  12. 2021Computational Imaging and Artificial Intelligence: The Next Revolution of Mobile Visioncited by 7
7 more
  1. 2023DiffSCI: Zero-Shot Snapshot Compressive Imaging via Iterative Spectral Diffusion Modelcited by 6
  2. 2022Spectral Compressive Imaging Reconstruction Using Convolution and Contextual Transformercited by 4
  3. 2021Deep-learning-based Hyperspectral imaging through a RGB cameracited by 2
  4. 2024Dual Hyperspectral Mamba for Efficient Spectral Compressive Imagingcited by 2
  5. 2021A Simple and Efficient Reconstruction Backbone for Snapshot Compressive Imagingcited by 1
  6. 2024Inter and Intra Prior Learning-based Hyperspectral Image Reconstruction Using Snapshot SWIR Metasurfacecited by 1
  7. 2021Snapshot Compressive Imaging: Principle, Implementation, Theory, Algorithms and Applicationscited by 0