Whiteness constraints in a unified variational framework for image restoration
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Publication:1799621
DOI10.1007/s10851-018-0845-6zbMath1433.94014OpenAlexW2891127710WikidataQ113106927 ScholiaQ113106927MaRDI QIDQ1799621
Federica Sciacchitano, Fiorella Sgallari, Serena Morigi, Alessandro Lanza
Publication date: 19 October 2018
Published in: Journal of Mathematical Imaging and Vision (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/11585/653482
ADMMtotal variationadditive white noisevariational image restorationnon-convex non-smooth optimization
Applications of mathematical programming (90C90) Nonconvex programming, global optimization (90C26) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)
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Residual whiteness principle for automatic parameter selection in \(\ell_2-\ell_2\) image super-resolution problems, Ternary image decomposition with automatic parameter selection via auto- and cross-correlation, Multivariate Myriad Filters Based on Parameter Estimation of Student-$t$ Distributions, ADMM-based residual whiteness principle for automatic parameter selection in single image super-resolution problems, On and Beyond Total Variation Regularization in Imaging: The Role of Space Variance, Residual whiteness principle for parameter-free image restoration, Alternatives to the EM algorithm for ML estimation of location, scatter matrix, and degree of freedom of the Student \(t\) distribution, Automatic parameter selection based on residual whiteness for convex non-convex variational restoration, A comparison of parameter choice rules for \(\ell^p\)-\(\ell^q\) minimization
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