SPIRAL
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Related Items (26)
On some steplength approaches for proximal algorithms ⋮ A combined higher order non-convex total variation with overlapping group sparsity for Poisson noise removal ⋮ Signal Recovery and System Calibration from Multiple Compressive Poisson Measurements ⋮ Poisson Noise Reduction with Higher-Order Natural Image Prior Model ⋮ Patch-Based Image Restoration Using Expectation Propagation ⋮ Composite Self-Concordant Minimization ⋮ A new steplength selection for scaled gradient methods with application to image deblurring ⋮ Some proximal methods for Poisson intensity CBCT and PET ⋮ A novel sparsity reconstruction method from Poisson data for 3D bioluminescence tomography ⋮ Iterative reweighted total generalized variation based Poisson noise removal model ⋮ Joint reconstruction via coupled Bregman iterations with applications to PET-MR imaging ⋮ This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice ⋮ Convergence of Inexact Forward--Backward Algorithms Using the Forward--Backward Envelope ⋮ Composite convex optimization with global and local inexact oracles ⋮ Unnamed Item ⋮ Poisson noise reduction with non-local PCA ⋮ Point process estimation with Mirror Prox algorithms ⋮ Variance-stabilization-based compressive inversion under Poisson or Poisson–Gaussian noise with analytical bounds ⋮ Inertial Variable Metric Techniques for the Inexact Forward--Backward Algorithm ⋮ A block coordinate variable metric linesearch based proximal gradient method ⋮ ACQUIRE: an inexact iteratively reweighted norm approach for TV-based Poisson image restoration ⋮ A Variable Metric Forward-Backward Method with Extrapolation ⋮ String-averaging incremental subgradients for constrained convex optimization with applications to reconstruction of tomographic images ⋮ Nonconvex Optimization for 3-Dimensional Point Source Localization Using a Rotating Point Spread Function ⋮ Scaled, Inexact, and Adaptive Generalized FISTA for Strongly Convex Optimization ⋮ Estimation of a delta-contaminated density of a random intensity of Poisson data
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