SPIRAL

The Sparse Poisson Intensity Reconstruction ALgorithms (SPIRAL) toolbox, SPIRALTAP, is MATLAB code for recovering sparse signals from Poisson observations. SPIRAL minimizes a regularized negative log-likelihood objective function with various penalty choices for the regularization terms:

Keywords for this software

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References in zbMATH (referenced in 22 articles )

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  1. Bonettini, S.; Prato, M.; Rebegoldi, S.: Convergence of inexact forward-backward algorithms using the forward-backward envelope (2020)
  2. di Serafino, Daniela; Landi, Germana; Viola, Marco: ACQUIRE: an inexact iteratively reweighted norm approach for TV-based Poisson image restoration (2020)
  3. He, Niao; Harchaoui, Zaid; Wang, Yichen; Song, Le: Point process estimation with Mirror Prox algorithms (2020)
  4. Sun, Tianxiao; Necoara, Ion; Tran-Dinh, Quoc: Composite convex optimization with global and local inexact oracles (2020)
  5. Bohra, Pakshal; Garg, Deepak; Gurumoorthy, Karthik S.; Rajwade, Ajit: Variance-stabilization-based compressive inversion under Poisson or Poisson-Gaussian noise with analytical bounds (2019)
  6. Wang, Chao; Chan, Raymond; Nikolova, Mila; Plemmons, Robert; Prasad, Sudhakar: Nonconvex optimization for 3-dimensional point source localization using a rotating point spread function (2019)
  7. Bonettini, S.; Prato, M.; Rebegoldi, S.: A block coordinate variable metric linesearch based proximal gradient method (2018)
  8. Bonettini, S.; Rebegoldi, S.; Ruggiero, V.: Inertial variable metric techniques for the inexact forward-backward algorithm (2018)
  9. Rasch, Julian; Brinkmann, Eva-Maria; Burger, Martin: Joint reconstruction via coupled Bregman iterations with applications to PET-MR imaging (2018)
  10. Bonettini, S.; Porta, F.; Ruggiero, V.: A variable metric forward-backward method with extrapolation (2016)
  11. De Canditiis, Daniela; Pensky, Marianna: Estimation of a delta-contaminated density of a random intensity of Poisson data (2016)
  12. de Oliveira, Rafael Massambone; Helou, Elias Salomão; Costa, Eduardo Fontoura: String-averaging incremental subgradients for constrained convex optimization with applications to reconstruction of tomographic images (2016)
  13. Feng, Wensen; Qiao, Hong; Chen, Yunjin: Poisson noise reduction with higher-order natural image prior model (2016)
  14. Porta, Federica; Loris, Ignace: On some steplength approaches for proximal algorithms (2015)
  15. Porta, Federica; Prato, Marco; Zanni, Luca: A new steplength selection for scaled gradient methods with application to image deblurring (2015)
  16. Quoc, Tran-Dinh; Kyrillidis, Anastasios; Cevher, Volkan: Composite self-concordant minimization (2015)
  17. Wang, Liming; Huang, Jiaji; Yuan, Xin; Krishnamurthy, Kalyani; Greenberg, Joel; Cevher, Volkan; Rodrigues, Miguel R. D.; Brady, David; Calderbank, Robert; Carin, Lawrence: Signal recovery and system calibration from multiple compressive Poisson measurements (2015)
  18. Salmon, Joseph; Harmany, Zachary; Deledalle, Charles-Alban; Willett, Rebecca: Poisson noise reduction with non-local PCA (2014)
  19. Wang, Xu-dong; Feng, Xiang-chu; Wang, Wei-wei; Zhang, Wen-juan: Iterative reweighted total generalized variation based Poisson noise removal model (2013)
  20. Anthoine, Sandrine; Aujol, Jean-François; Boursier, Yannick; Mélot, Clothilde: Some proximal methods for Poisson intensity CBCT and PET (2012)

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