Boosting of Image Denoising Algorithms

DOI10.1137/140990978zbMath1341.94006arXiv1502.06220OpenAlexW1829781029MaRDI QIDQ3192649

Yaniv Romano, Michael Elad

Publication date: 13 October 2015

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

Full work available at URL: https://arxiv.org/abs/1502.06220

zbMATH Keywords

regularizationgraph theorydenoisingimage restorationboostingsparse representationgraph LaplacianK-SDV

Mathematics Subject Classification ID

Image analysis in multivariate analysis (62H35) Graphs and linear algebra (matrices, eigenvalues, etc.) (05C50) Image processing (compression, reconstruction, etc.) in information and communication theory (94A08) Linear operators and ill-posed problems, regularization (47A52)

Related Items (12)

Total generalized variation for triangulated surface data ⋮ Content-aware compressive sensing recovery using Laplacian scale mixture priors and side information ⋮ Block-based refitting in \(\ell_{12}\) sparse regularization ⋮ Patch Ordering as a Regularization for Inverse Problems in Image Processing ⋮ Illumination problems in digital images. A statistical point of view ⋮ The Little Engine that Could: Regularization by Denoising (RED) ⋮ An adaptive boosting algorithm for image denoising ⋮ A unified view on patch aggregation ⋮ Rendition: Reclaiming What a Black Box Takes Away ⋮ An hybrid denoising algorithm based on directional wavelet packets ⋮ CLEAR: Covariant LEAst-Square Refitting with Applications to Image Restoration ⋮ A Novel Mesh Denoising Method Based on Relaxed Second-Order Total Generalized Variation

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