EDP Sciences logo
Subscriber Authentication Point
Search
Menu
Home All issues Volume 697 (May 2025) A&A, 697 (2025) A136 References
Open Access
Issue
A&A
Volume 697, May 2025
Article Number A136
Number of page(s) 12
Section Numerical methods and codes
DOI https://doi.org/10.1051/0004-6361/202452308
Published online 16 May 2025
  1. Abolfathi, B., Alonso, D., Armstrong, R., et al. 2021, ApJS, 253, 31 [CrossRef] [Google Scholar]
  2. Agustsson, E., & Timofte, R. 2017, in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 1122 [CrossRef] [Google Scholar]
  3. Akhaury, U., Starck, J.-L., Jablonka, P., Courbin, F., & Michalewicz, K. 2022, Front. Astron. Space Sci., 9, 1001043 [Google Scholar]
  4. Akhaury, U., Jablonka, P., Starck, J.-L., & Courbin, F. 2024, A&A, 688, A6 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  5. Beck, A., & Teboulle, M. 2009, SIAM J. Imag. Sci., 2, 183 [CrossRef] [Google Scholar]
  6. Bigdeli, S. A., Jin, M., Favaro, P., & Zwicker, M. 2017, in Proceedings of the 31st International Conference on Neural Information Processing Systems, NIPS’ 17 (USA: Curran Associates Inc.), 763 [Google Scholar]
  7. Boyd, S., Parikh, N., Chu, E., Peleato, B., & Eckstein, J. 2010, Mach. Learn., 3, 1 [Google Scholar]
  8. Cantale, N., Courbin, F., Tewes, M., Jablonka, P., & Meylan, G. 2016, A&A, 589, A81 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  9. Chan, S. H., Wang, X., & Elgendy, O. A., 2017, IEEE Trans. Computat. Imag., 3, 84 [Google Scholar]
  10. Chen, Y., & Pock, T. 2017, IEEE Trans. Pattern Anal. Mach. Intell., 39, 1256 [Google Scholar]
  11. Donath, A., Siemiginowska, A., Kashyap, V., Dyk, D. V., & Burke, D. 2023, Bull. AAS, 55, 4 [Google Scholar]
  12. Euclid Collaboration (Scaramella, R., et al.) 2022, A&A, 662, A112 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  13. Fan, C.-M., Liu, T.-J., & Liu, K.-H. 2022, in 2022 IEEE International Symposium on Circuits and Systems (ISCAS) (IEEE) [Google Scholar]
  14. Gupta, H., Jin, K. H., Nguyen, H. Q., McCann, M. T., & Unser, M. 2018, IEEE Trans. Med. Imag., 37, 1440 [Google Scholar]
  15. He, K., Zhang, X., Ren, S., & Sun, J. 2016, in 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 770 [Google Scholar]
  16. Ingaramo, M., York, A. G., Hoogendoorn, E., et al. 2014, ChemPhysChem, 15, 794 [Google Scholar]
  17. Joseph, R., Melchior, P., & Moolekamp, F. 2021, arXiv e-prints [arXiv:2107.06984] [Google Scholar]
  18. Liaudat, T., Starck, J.-L., Kilbinger, M., & Frugier, P.-A. 2022, Inverse Problems, 39, 035008 [Google Scholar]
  19. Lim, B., Son, S., Kim, H., Nah, S., & Lee, K. M. 2017, in 2017 IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 1132 [CrossRef] [Google Scholar]
  20. Lucy, L. B. 1974, AJ, 79, 745 [Google Scholar]
  21. Ma, K., Duanmu, Z., Wu, Q., et al. 2017, IEEE Trans. Image Process., 26, 1004 [Google Scholar]
  22. Magain, P., Courbin, F., & Sohy, S. 1998, ApJ, 494, 472 [NASA ADS] [CrossRef] [Google Scholar]
  23. Meinhardt, T., Moller, M., Hazirbas, C., & Cremers, D. 2017, in Proceedings of the IEEE International Conference on Computer Vision, 1781 [Google Scholar]
  24. Michalewicz, K., Millon, M., Dux, F., & Courbin, F. 2023, J. Open Source Softw., 8, 5340 [NASA ADS] [CrossRef] [Google Scholar]
  25. Nammour, F., Akhaury, U., Girard, J. N., et al. 2022, A&A, 663, A69 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  26. Ramzi, Z., Michalewicz, K., Starck, J.-L., Moreau, T., & Ciuciu, P. 2023, J. Math. Imag. Vis., 65, 240 [Google Scholar]
  27. Retzlaff, J., Rosati, P., Dickinson, M., et al. 2010, A&A, 511, A50 [NASA ADS] [CrossRef] [EDP Sciences] [Google Scholar]
  28. Richardson, W. H. 1972, J. Opt. Soc. Am., 62, 55 [NASA ADS] [CrossRef] [Google Scholar]
  29. Ronneberger, O., Fischer, P., & Brox, T. 2015, arXiv e-prints [arXiv:1505.04597] [Google Scholar]
  30. Skilling, J., & Bryan, R. K. 1984, MNRAS, 211, 111 [NASA ADS] [CrossRef] [Google Scholar]
  31. Sreehari, S., Venkatakrishnan, S., Wohlberg, B., et al. 2016, IEEE Trans. Computat. Imag., 2, 408 [Google Scholar]
  32. Starck, J.-L., Murtagh, F., & Bertero, M. 2015, Starlet Transform in Astronomical Data Processing, ed. O. Scherzer (New York, NY: Springer New York), 2053 [Google Scholar]
  33. Sureau, F., Lechat, A., & Starck, J.-L. 2020, A&A, 641, A67 [EDP Sciences] [Google Scholar]
  34. Tikhonov, A. N., & Arsenin, V. Y. 1977, Solutions of Ill-posed Problems (Washington, D.C.: John Wiley & Sons, New York: V. H. Winston & Sons), xiii +258, translated from the Russian, Preface by translation editor Fritz John, Scripta Series in Mathematics [Google Scholar]
  35. van der Walt, S., Schönberger, J. L., Nunez-Iglesias, J., et al. 2014, arXiv e-prints [arXiv:1407.6245] [Google Scholar]
  36. Venkatakrishnan, S. V., Bouman, C. A., & Wohlberg, B. 2013, 2013 IEEE Global Conference on Signal and Information Processing, 945 [CrossRef] [Google Scholar]
  37. Venkatesh, G. M., Naresh, Y. G., Little, S., & O’Connor, N. E. 2018, in OR 2.0/CARE/CLIP/ISIC@MICCAI [Google Scholar]
  38. Željko Ivezić, Kahn, S. M., Tyson, J. A., et al. 2019, ApJ, 873, 111 [NASA ADS] [CrossRef] [Google Scholar]
  39. Zhang, K., Zuo, W., & Zhang, L. 2018a, IEEE Trans. Image Process., 27, 4608 [Google Scholar]
  40. Zhang, Z., Liu, Q., & Wang, Y. 2018b, IEEE Geosci. Remote Sens. Lett., 15, 749 [CrossRef] [Google Scholar]
  41. Zhang, K., Li, Y., Zuo, W., et al. 2022, IEEE Trans. Pattern Anal. Mach. Intell., 44, 6360 [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.