FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2912581987> ?p ?o ?g. }

• W2912581987 endingPage "489" @default.
• W2912581987 startingPage "485" @default.
• W2912581987 abstract "In this letter, a sparse representation (SR) model named convolutional sparsity based morphological component analysis (CS-MCA) is introduced for pixel-level medical image fusion. Unlike the standard SR model, which is based on single image component and overlapping patches, the CS-MCA model can simultaneously achieve multi-component and global SRs of source images, by integrating MCA and convolutional sparse representation (CSR) into a unified optimization framework. For each source image, in the proposed fusion method, the CSRs of its cartoon and texture components are first obtained by the CS-MCA model using pre-learned dictionaries. Then, for each image component, the sparse coefficients of all the source images are merged and the fused component is accordingly reconstructed using the corresponding dictionary. Finally, the fused image is calculated as the superposition of the fused cartoon and texture components. Experimental results demonstrate that the proposed method can outperform some benchmarking and state-of-the-art SR-based fusion methods in terms of both visual perception and objective assessment." @default.
• W2912581987 created "2019-02-21" @default.
• W2912581987 creator A5009277467 @default.
• W2912581987 creator A5028143781 @default.
• W2912581987 creator A5051587486 @default.
• W2912581987 creator A5083857025 @default.
• W2912581987 date "2019-03-01" @default.
• W2912581987 modified "2023-10-17" @default.
• W2912581987 title "Medical Image Fusion via Convolutional Sparsity Based Morphological Component Analysis" @default.
• W2912581987 cites W1560910787 @default.
• W2912581987 cites W1563899710 @default.
• W2912581987 cites W1965557194 @default.
• W2912581987 cites W1970758811 @default.
• W2912581987 cites W1985972181 @default.
• W2912581987 cites W1986517950 @default.
• W2912581987 cites W1994607540 @default.
• W2912581987 cites W1994714721 @default.
• W2912581987 cites W1996278907 @default.
• W2912581987 cites W1997480692 @default.
• W2912581987 cites W1999316653 @default.
• W2912581987 cites W2005073548 @default.
• W2912581987 cites W2023844059 @default.
• W2912581987 cites W2026916126 @default.
• W2912581987 cites W2066667210 @default.
• W2912581987 cites W2067977604 @default.
• W2912581987 cites W2068941797 @default.
• W2912581987 cites W2091484864 @default.
• W2912581987 cites W2094824638 @default.
• W2912581987 cites W2108283046 @default.
• W2912581987 cites W2114207195 @default.
• W2912581987 cites W2116702374 @default.
• W2912581987 cites W2131168375 @default.
• W2912581987 cites W2142060261 @default.
• W2912581987 cites W2146353910 @default.
• W2912581987 cites W2168783614 @default.
• W2912581987 cites W2179019672 @default.
• W2912581987 cites W2190662802 @default.
• W2912581987 cites W2266694576 @default.
• W2912581987 cites W2306859282 @default.
• W2912581987 cites W2474462684 @default.
• W2912581987 cites W2522703671 @default.
• W2912581987 cites W2532801510 @default.
• W2912581987 cites W2557682050 @default.
• W2912581987 cites W2559870345 @default.
• W2912581987 cites W2589073776 @default.
• W2912581987 cites W2620889673 @default.
• W2912581987 cites W2624240493 @default.
• W2912581987 cites W2746410086 @default.
• W2912581987 cites W2751011928 @default.
• W2912581987 cites W2773950452 @default.
• W2912581987 cites W2776654051 @default.
• W2912581987 cites W2793890232 @default.
• W2912581987 cites W2806456004 @default.
• W2912581987 cites W2898653582 @default.
• W2912581987 cites W4235713725 @default.
• W2912581987 doi "https://doi.org/10.1109/lsp.2019.2895749" @default.
• W2912581987 hasPublicationYear "2019" @default.
• W2912581987 type Work @default.
• W2912581987 sameAs 2912581987 @default.
• W2912581987 citedByCount "173" @default.
• W2912581987 countsByYear W29125819872019 @default.
• W2912581987 countsByYear W29125819872020 @default.
• W2912581987 countsByYear W29125819872021 @default.
• W2912581987 countsByYear W29125819872022 @default.
• W2912581987 countsByYear W29125819872023 @default.
• W2912581987 crossrefType "journal-article" @default.
• W2912581987 hasAuthorship W2912581987A5009277467 @default.
• W2912581987 hasAuthorship W2912581987A5028143781 @default.
• W2912581987 hasAuthorship W2912581987A5051587486 @default.
• W2912581987 hasAuthorship W2912581987A5083857025 @default.
• W2912581987 hasConcept C115961682 @default.
• W2912581987 hasConcept C121332964 @default.
• W2912581987 hasConcept C124504099 @default.
• W2912581987 hasConcept C138885662 @default.
• W2912581987 hasConcept C153180895 @default.
• W2912581987 hasConcept C154945302 @default.
• W2912581987 hasConcept C158525013 @default.
• W2912581987 hasConcept C168167062 @default.
• W2912581987 hasConcept C27438332 @default.
• W2912581987 hasConcept C2780692498 @default.
• W2912581987 hasConcept C31972630 @default.
• W2912581987 hasConcept C41008148 @default.
• W2912581987 hasConcept C41895202 @default.
• W2912581987 hasConcept C51432778 @default.
• W2912581987 hasConcept C69744172 @default.
• W2912581987 hasConcept C81363708 @default.
• W2912581987 hasConcept C97355855 @default.
• W2912581987 hasConceptScore W2912581987C115961682 @default.
• W2912581987 hasConceptScore W2912581987C121332964 @default.
• W2912581987 hasConceptScore W2912581987C124504099 @default.
• W2912581987 hasConceptScore W2912581987C138885662 @default.
• W2912581987 hasConceptScore W2912581987C153180895 @default.
• W2912581987 hasConceptScore W2912581987C154945302 @default.
• W2912581987 hasConceptScore W2912581987C158525013 @default.
• W2912581987 hasConceptScore W2912581987C168167062 @default.
• W2912581987 hasConceptScore W2912581987C27438332 @default.
• W2912581987 hasConceptScore W2912581987C2780692498 @default.
• W2912581987 hasConceptScore W2912581987C31972630 @default.

• next