Residual whiteness principle for automatic parameter selection in \(\ell_2-\ell_2\) image super-resolution problems

DOI10.1007/978-3-030-75549-2_38zbMath1487.94029arXiv2104.01001OpenAlexW3164950756MaRDI QIDQ826216

Fiorella Sgallari, Alessandro Lanza, Luca Calatroni, Monica Pragliola

Publication date: 20 December 2021

Full work available at URL: https://arxiv.org/abs/2104.01001

zbMATH Keywords

single image super-resolutionadaptive parameter selectionresidual whiteness principle

Mathematics Subject Classification ID

Computing methodologies for image processing (68U10) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (4)

Automatic fidelity and regularization terms selection in variational image restoration ⋮ Whiteness-based parameter selection for Poisson data in variational image processing ⋮ A Zeroth-Order Proximal Stochastic Gradient Method for Weakly Convex Stochastic Optimization ⋮ ADMM-based residual whiteness principle for automatic parameter selection in single image super-resolution problems

Cites Work

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• Whiteness constraints in a unified variational framework for image restoration
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• Fast Single Image Super-Resolution Using a New Analytical Solution for <inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math> </inline-formula>–<inline-formula> <tex-math notation="LaTeX">$\ell _{2}$ </tex-math> </inline-formula> Problems

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