FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W260788981> ?p ?o ?g. }

• W260788981 endingPage "2682" @default.
• W260788981 startingPage "2662" @default.
• W260788981 abstract "The Poisson--Gaussian model can accurately describe the noise present in a number of imaging systems. However most existing restoration methods rely on approximations of the Poisson--Gaussian noise statistics. We propose a convex optimization strategy for the reconstruction of images degraded by a linear operator and corrupted with a mixed Poisson--Gaussian noise. The originality of our approach consists of considering the exact, mixed continuous-discrete model corresponding to the data statistics. After establishing the Lipschitz differentiability and convexity of the Poisson--Gaussian neg-log-likelihood, we derive a primal-dual iterative scheme for minimizing the associated penalized criterion. The proposed method is applicable to a large choice of convex penalty terms. The robustness of our scheme allows us to handle computational difficulties due to infinite sums arising from the computation of the gradient of the criterion. We propose finite bounds for these sums, that are dependent on the current image estimate, and thus adapted to each iteration of our algorithm. The proposed approach is validated on image restoration examples. Then, the exact data fidelity term is used as a reference for studying some of its various approximations. We show that in a variational framework the shifted Poisson and exponential approximations lead to very good restoration results." @default.
• W260788981 created "2016-06-24" @default.
• W260788981 creator A5002452272 @default.
• W260788981 creator A5062777204 @default.
• W260788981 creator A5062845079 @default.
• W260788981 creator A5086251368 @default.
• W260788981 date "2015-01-01" @default.
• W260788981 modified "2023-10-15" @default.
• W260788981 title "A Convex Approach for Image Restoration with Exact Poisson--Gaussian Likelihood" @default.
• W260788981 cites W1423203725 @default.
• W260788981 cites W1922442141 @default.
• W260788981 cites W1953936588 @default.
• W260788981 cites W1981112674 @default.
• W260788981 cites W1981851117 @default.
• W260788981 cites W1998339281 @default.
• W260788981 cites W1998991750 @default.
• W260788981 cites W2006262045 @default.
• W260788981 cites W2007437458 @default.
• W260788981 cites W2009204854 @default.
• W260788981 cites W2011194005 @default.
• W260788981 cites W2013388817 @default.
• W260788981 cites W2018612061 @default.
• W260788981 cites W2019569173 @default.
• W260788981 cites W2021548137 @default.
• W260788981 cites W2022377207 @default.
• W260788981 cites W2027051720 @default.
• W260788981 cites W2030254567 @default.
• W260788981 cites W2030322422 @default.
• W260788981 cites W2037252428 @default.
• W260788981 cites W2038497950 @default.
• W260788981 cites W2055467852 @default.
• W260788981 cites W2055834582 @default.
• W260788981 cites W2056578325 @default.
• W260788981 cites W2060331468 @default.
• W260788981 cites W2060945009 @default.
• W260788981 cites W2062271656 @default.
• W260788981 cites W2080744942 @default.
• W260788981 cites W2092663520 @default.
• W260788981 cites W2103559027 @default.
• W260788981 cites W2107844156 @default.
• W260788981 cites W2107941784 @default.
• W260788981 cites W2108855378 @default.
• W260788981 cites W2114423093 @default.
• W260788981 cites W2124682210 @default.
• W260788981 cites W2125852763 @default.
• W260788981 cites W2133665775 @default.
• W260788981 cites W2135780853 @default.
• W260788981 cites W2136035751 @default.
• W260788981 cites W2137534136 @default.
• W260788981 cites W2142280715 @default.
• W260788981 cites W2147068866 @default.
• W260788981 cites W2151514667 @default.
• W260788981 cites W2151841537 @default.
• W260788981 cites W2154707635 @default.
• W260788981 cites W2155574073 @default.
• W260788981 cites W2156600062 @default.
• W260788981 cites W2160924560 @default.
• W260788981 cites W2165437406 @default.
• W260788981 cites W2333280117 @default.
• W260788981 cites W3100489614 @default.
• W260788981 cites W3104072696 @default.
• W260788981 cites W3105465707 @default.
• W260788981 cites W3106359998 @default.
• W260788981 cites W4205213118 @default.
• W260788981 doi "https://doi.org/10.1137/15m1014395" @default.
• W260788981 hasPublicationYear "2015" @default.
• W260788981 type Work @default.
• W260788981 sameAs 260788981 @default.
• W260788981 citedByCount "73" @default.
• W260788981 countsByYear W2607889812014 @default.
• W260788981 countsByYear W2607889812016 @default.
• W260788981 countsByYear W2607889812017 @default.
• W260788981 countsByYear W2607889812018 @default.
• W260788981 countsByYear W2607889812019 @default.
• W260788981 countsByYear W2607889812020 @default.
• W260788981 countsByYear W2607889812021 @default.
• W260788981 countsByYear W2607889812022 @default.
• W260788981 countsByYear W2607889812023 @default.
• W260788981 crossrefType "journal-article" @default.
• W260788981 hasAuthorship W260788981A5002452272 @default.
• W260788981 hasAuthorship W260788981A5062777204 @default.
• W260788981 hasAuthorship W260788981A5062845079 @default.
• W260788981 hasAuthorship W260788981A5086251368 @default.
• W260788981 hasBestOaLocation W2607889812 @default.
• W260788981 hasConcept C100906024 @default.
• W260788981 hasConcept C105795698 @default.
• W260788981 hasConcept C106159729 @default.
• W260788981 hasConcept C106430172 @default.
• W260788981 hasConcept C112680207 @default.
• W260788981 hasConcept C11413529 @default.
• W260788981 hasConcept C115961682 @default.
• W260788981 hasConcept C121332964 @default.
• W260788981 hasConcept C126255220 @default.
• W260788981 hasConcept C134306372 @default.
• W260788981 hasConcept C154945302 @default.
• W260788981 hasConcept C157972887 @default.
• W260788981 hasConcept C162324750 @default.
• W260788981 hasConcept C163716315 @default.

• next