A new steplength selection for scaled gradient methods with application to image deblurring
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Publication:897119
DOI10.1007/s10915-015-9991-9zbMath1328.65138arXiv1407.2375OpenAlexW2030583950MaRDI QIDQ897119
Federica Porta, Marco Prato, Luca Zanni
Publication date: 17 December 2015
Published in: Journal of Scientific Computing (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1407.2375
Numerical mathematical programming methods (65K05) Large-scale problems in mathematical programming (90C06) Computing methodologies for image processing (68U10) Numerical methods for inverse problems for integral equations (65R32)
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Cites Work
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- Nonlinear total variation based noise removal algorithms
- An efficient gradient method using the Yuan steplength
- Duality-based algorithms for total-variation-regularized image restoration
- A limited memory steepest descent method
- Gradient methods with adaptive step-sizes
- New adaptive stepsize selections in gradient methods
- An algorithm for total variation minimization and applications
- A modified projection algorithm for large strictly-convex quadratic programs
- A first-order primal-dual algorithm for convex problems with applications to imaging
- On the convergence of primal-dual hybrid gradient algorithms for total variation image restoration
- A convergent blind deconvolution method for post-adaptive-optics astronomical imaging
- On spectral properties of steepest descent methods
- Scaling techniques for gradient projection-type methods in astronomical image deblurring
- A discrepancy principle for Poisson data
- An alternating extragradient method for total variation-based image restoration from Poisson data
- Regularization parameter selection methods for ill-posed Poisson maximum likelihood estimation
- Deblurring Images
- A scaled gradient projection method for constrained image deblurring
- Efficient gradient projection methods for edge-preserving removal of Poisson noise
- Two-Point Step Size Gradient Methods
- Analysis of bounded variation penalty methods for ill-posed problems
- Rank-Deficient and Discrete Ill-Posed Problems
- Alternate minimization gradient method
- Inexact spectral projected gradient methods on convex sets
- A Nonmonotone Line Search Technique for Newton’s Method
- Computational Methods for Inverse Problems
- Penalized maximum likelihood image restoration with positivity constraints: multiplicative algorithms
- An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds
- Nonnegative image reconstruction from sparse Fourier data: a new deconvolution algorithm
- Accelerated gradient methods for the x-ray imaging of solar flares
- This is SPIRAL-TAP: Sparse Poisson Intensity Reconstruction ALgorithms—Theory and Practice
- Sparse Poisson Noisy Image Deblurring
- On the filtering effect of iterative regularization algorithms for discrete inverse problems
- A general method to devise maximum-likelihood signal restoration multiplicative algorithms with non-negativity constraints.
