Reconstruction method of computationally convolutional ghost imaging based on total variation regularization.

Gu S, Zeng Y, Zuo H

DOI: 10.1364/josaa.599165
Published: 2026 Sep 1
Container: Journal of the Optical Society of America. A, Optics, image science, and vision
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1364/josaa.599165,
  title = {Reconstruction method of computationally convolutional ghost imaging based on total variation regularization.},
  author = {Gu S and Zeng Y and Zuo H},
  year = {2026},
  journal = {Journal of the Optical Society of America. A, Optics, image science, and vision},
  doi = {10.1364/josaa.599165},
  url = {https://doi.org/10.1364/josaa.599165}
}

RIS

TY  - JOUR
TI  - Reconstruction method of computationally convolutional ghost imaging based on total variation regularization.
AU  - Gu S
AU  - Zeng Y
AU  - Zuo H
PY  - 2026
JO  - Journal of the Optical Society of America. A, Optics, image science, and vision
DO  - 10.1364/josaa.599165
UR  - https://doi.org/10.1364/josaa.599165
ER  -

APA

S, G., Y, Z., & H, Z. (2026). Reconstruction method of computationally convolutional ghost imaging based on total variation regularization.. Journal of the Optical Society of America. A, Optics, image science, and vision. https://doi.org/10.1364/josaa.599165

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pubmed · retrieved 2026-11-10T07:28:53.628Z