Symmetrizing Smoothing Filters

DOI10.1137/120875843zbMath1370.62024OpenAlexW1963816084MaRDI QIDQ2873195

Peyman Milanfar

Publication date: 23 January 2014

Published in: SIAM Journal on Imaging Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1137/120875843

zbMATH Keywords

filteringstochastic matricesLaplacian operatornonparametric regressionpositive matricesdata smoothingapplications of graph theoryapplications of Markov chains

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Filtering in stochastic control theory (93E11) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08)

Related Items (9)

Asymptotic Performance of Global Denoising ⋮ Scaling positive random matrices: concentration and asymptotic convergence ⋮ Robust Inference of Manifold Density and Geometry by Doubly Stochastic Scaling ⋮ On maximum a posteriori estimation with Plug \& Play priors and stochastic gradient descent ⋮ Image labeling by assignment ⋮ Demystifying the asymptotic behavior of global denoising ⋮ Single image super-resolution via non-local normalized graph Laplacian regularization: a self-similarity tribute ⋮ The Little Engine that Could: Regularization by Denoising (RED) ⋮ Rendition: Reclaiming What a Black Box Takes Away

This page was built for publication: Symmetrizing Smoothing Filters