Fetching the paper…
Reading the bibliography…
Optimized sensing is important for computational imaging in low-resource environments, when images must be recovered from severely limited measurements.
C. E. Shannon, “Communication in the presence of noise,” Proceedings of the IRE , vol. 37, no. 1, pp. 10–21, 1949
1949
Earlier work this paper cites.
J. Skilling and R. Bryan, “Maximum entropy image reconstruction-general algorithm,” Monthly notices of the royal astronomical society , vol. 211, p. 111, 1984
1984
Earlier work this paper cites.
A. R. Thompson, J. M. Moran, G. W. Swenson et al. , Interferometry and synthesis in radio astronomy . Wiley New York et al., 1986
1986
Earlier work this paper cites.
C. Bouman and K. Sauer, “A generalized gaussian image model for edge-preserving map estimation,” IEEE Transactions on image processing , vol. 2, no. 3, pp. 296–310, 1993
1993
Earlier work this paper cites.
D. Woody, “Radio interferometer array point spread functions i. theory and statistics,” ALMA Memo Series , vol. 389, 2001
2001
Earlier work this paper cites.
F. Boone, “Interferometric array design: Optimizing the locations of the antenna pads,” Astronomy & Astrophysics , vol. 377, no. 1, pp. 368–376, 2001
2001
Earlier work this paper cites.
G. Olague and R. Mohr, “Optimal camera placement for accurate reconstruction,” Pattern recognition , vol. 35, no. 4, pp. 927–944, 2002
2002
Earlier work this paper cites.
E. J. Candes, J. Romberg, and T. Tao, “Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information,” IEEE Transactions on Information Theory , vol. 52, no. 2, pp. 489–509, Feb 2006
2006
Earlier work this paper cites.
M. Lustig, D. Donoho, and J. M. Pauly, “Sparse mri: The application of compressed sensing for rapid mr imaging,” Magnetic Resonance in Medicine , vol. 58, no. 6, pp. 1182–1195, 2007. [Online]. Available: https://onlinelibrary.wiley.com/doi/abs/10.1002/mrm.21391
2007
Earlier work this paper cites.
E. Candes and J. Romberg, “Sparsity and incoherence in compressive sampling,” Inverse problems , vol. 23, no. 3, p. 969, 2007
2007
Earlier work this paper cites.
M. Lustig, D. L. Donoho, J. M. Santos, and J. M. Pauly, “Compressed sensing mri,” IEEE signal processing magazine , vol. 25, no. 2, p. 72, 2008
2008
Earlier work this paper cites.
E. J. Candès and M. B. Wakin, “An introduction to compressive sampling [a sensing/sampling paradigm that goes against the common knowledge in data acquisition],” IEEE signal processing magazine , vol. 25, no. 2, pp. 21–30, 2008
2008
Earlier work this paper cites.
S. V. Venkatakrishnan, C. A. Bouman, and B. Wohlberg, “Plug-and-play priors for model based reconstruction,” in 2013 IEEE Global Conference on Signal and Information Processing . IEEE, 2013, pp. 945–948
2013
Earlier work this paper cites.
2014
Cited alongside, same era.
L. Tian, Z. Liu, L.-H. Yeh, M. Chen, J. Zhong, and L. Waller, “Computational illumination for high-speed in vitro fourier ptychographic microscopy,” Optica , vol. 2, no. 10, pp. 904–911, 2015
2015
Cited alongside, same era.
O. Ronneberger, P. Fischer, and T. Brox, “U-net: Convolutional networks for biomedical image segmentation,” in International Conference on Medical image computing and computer-assisted intervention . Springer, 2015, pp. 234–241
2015
Cited alongside, same era.
K. L. Bouman, M. D. Johnson, D. Zoran, V. L. Fish, S. S. Doeleman, and W. T. Freeman, “Computational imaging for vlbi image reconstruction,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2016, pp. 913–922
2016
Cited alongside, same era.
E. Kobler, M. Muckley, B. Chen, F. Knoll, K. Hammernik, T. Pock, D. Sodickson, and R. Otazo, “Variational deep learning for low-dose computed tomography,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2018, pp. 6687–6691
2018
Later among the works it cites.
K. L. Bouman, M. D. Johnson, A. V. Dalca, A. A. Chael, F. Roelofs, S. S. Doeleman, and W. T. Freeman, “Reconstructing video of time-varying sources from radio interferometric measurements,” IEEE Transactions on Computational Imaging , vol. 4, no. 4, pp. 512–527, 2018
2018
Later among the works it cites.
H. Chen, J. Gu, O. Gallo, M.-Y. Liu, A. Veeraraghavan, and J. Kautz, “Reblur2deblur: Deblurring videos via self-supervised learning,” in 2018 IEEE International Conference on Computational Photography (ICCP) . IEEE, 2018, pp. 1–9
2018
Later among the works it cites.
K. Hammernik, T. Klatzer, E. Kobler, M. P. Recht, D. K. Sodickson, T. Pock, and F. Knoll, “Learning a variational network for reconstruction of accelerated mri data,” Magnetic resonance in medicine , vol. 79, no. 6, pp. 3055–3071, 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
A. Chakrabarti, “Learning sensor multiplexing design through back-propagation,” in Advances in Neural Information Processing Systems , 2016, pp. 3081–3089
2016
Cited alongside, same era.
J. Sun, H. Li, Z. Xu et al. , “Deep admm-net for compressive sensing mri,” in Advances in neural information processing systems , 2016, pp. 10–18
2016
Cited alongside, same era.
Y. Rivenson, Z. Göröcs, H. Günaydin, Y. Zhang, H. Wang, and A. Ozcan, “Deep learning microscopy,” Optica , vol. 4, no. 11, pp. 1437–1443, 2017
2017
Cited alongside, same era.
A. Sinha, J. Lee, S. Li, and G. Barbastathis, “Lensless computational imaging through deep learning,” Optica , vol. 4, no. 9, pp. 1117–1125, 2017
2017
Cited alongside, same era.
K. H. Jin, M. T. McCann, E. Froustey, and M. Unser, “Deep convolutional neural network for inverse problems in imaging,” IEEE Transactions on Image Processing , vol. 26, no. 9, pp. 4509–4522, 2017
2017
Cited alongside, same era.
2017
Cited alongside, same era.
D. Lee, J. Yoo, and J. C. Ye, “Deep residual learning for compressed sensing mri,” in 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017) . IEEE, 2017, pp. 15–18
2017
Cited alongside, same era.
2017
Cited alongside, same era.
2018
Later among the works it cites.
Y. P. X. D. S. B. W. H. F. H. G. W. V. Sitzmann, S. Diamond, “End-to-end optimization of optics and image processing for achromatic extended depth of field and super-resolution imaging,” ACM Trans. Graph. (SIGGRAPH) , 2018
2018
Later among the works it cites.
M. Yoshida, A. Torii, M. Okutomi, K. Endo, Y. Sugiyama, R.-i. Taniguchi, and H. Nagahara, “Joint optimization for compressive video sensing and reconstruction under hardware constraints,” in Proceedings of the European Conference on Computer Vision (ECCV) , 2018, pp. 634–649
2018
Later among the works it cites.
A. A. Chael, M. D. Johnson, K. L. Bouman, L. L. Blackburn, K. Akiyama, and R. Narayan, “Interferometric imaging directly with closure phases and closure amplitudes,” The Astrophysical Journal , vol. 857, no. 1, p. 23, 2018
2018
Later among the works it cites.
M. Kellman, E. Bostan, M. Chen, and L. Waller, “Data-driven design for fourier ptychographic microscopy,” in 2019 IEEE International Conference on Computational Photography (ICCP) . IEEE, 2019, pp. 1–8
2019
Later among the works it cites.
2019
Later among the works it cites.
2019
Later among the works it cites.
K. Akiyama, A. Alberdi, W. Alef, K. Asada, R. Azulay, A.-K. Baczko, D. Ball, M. Baloković, J. Barrett, D. Bintley et al. , “First m87 event horizon telescope results. iv. imaging the central supermassive black hole,” The Astrophysical Journal Letters , vol. 875, no. 1, p. L4, 2019
2019
Later among the works it cites.