Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386231105> ?p ?o ?g. }
- W4386231105 endingPage "1171" @default.
- W4386231105 startingPage "1167" @default.
- W4386231105 abstract "Most infrared and visible image fusion algorithms often struggle in dark environments where texture details in the visible image are largely obscured, although they are demon-strated to achieve good performance under normal illumination. To mitigate the dark environments issue, a novel Enlighten Fusion Multi-scale Network (EFMN) is proposed in this letter, which incorporates enhanced features at different scales into the main fusion network for lighting up the contexts in the darkness. With a sub-network enhancing the low-light visible image, multi-scale features are progressively enhanced and extracted. Then, a group of Fusion Modules (FM) are designed to fuse the features coarsely in multiple branches. Finally, the fused features are further refined by 1×1 convolution units to produce the resultant image. The processing of coarse fusion and then refinement at feature levels works effectively. Extensive experiments have shown that the proposed EFMN improves fusion performance in dark environments both subjectively and objectively. The improvements also facilitate typical down-stream vision tasks, such as object detection." @default.
- W4386231105 created "2023-08-29" @default.
- W4386231105 creator A5018866860 @default.
- W4386231105 creator A5019018136 @default.
- W4386231105 creator A5045137258 @default.
- W4386231105 date "2023-01-01" @default.
- W4386231105 modified "2023-09-27" @default.
- W4386231105 title "Enlighten Fusion Multiscale Network for Infrared and Visible Image Fusion in Dark Environments" @default.
- W4386231105 cites W1580389772 @default.
- W4386231105 cites W1994714721 @default.
- W4386231105 cites W2046119925 @default.
- W4386231105 cites W2056346283 @default.
- W4386231105 cites W2106002835 @default.
- W4386231105 cites W2116702374 @default.
- W4386231105 cites W2146353910 @default.
- W4386231105 cites W2164847484 @default.
- W4386231105 cites W2532801510 @default.
- W4386231105 cites W2606716941 @default.
- W4386231105 cites W2744070429 @default.
- W4386231105 cites W2809795042 @default.
- W4386231105 cites W2901100349 @default.
- W4386231105 cites W2912147220 @default.
- W4386231105 cites W2998012573 @default.
- W4386231105 cites W3011768656 @default.
- W4386231105 cites W3033116255 @default.
- W4386231105 cites W3043904761 @default.
- W4386231105 cites W3105639468 @default.
- W4386231105 cites W3108042295 @default.
- W4386231105 cites W3117326213 @default.
- W4386231105 cites W3120540810 @default.
- W4386231105 cites W3143068962 @default.
- W4386231105 cites W3159235206 @default.
- W4386231105 cites W3181367324 @default.
- W4386231105 cites W3182688976 @default.
- W4386231105 cites W3190808861 @default.
- W4386231105 cites W3194077607 @default.
- W4386231105 cites W3196742104 @default.
- W4386231105 cites W3198582484 @default.
- W4386231105 cites W3203030644 @default.
- W4386231105 cites W3213472242 @default.
- W4386231105 cites W4226178544 @default.
- W4386231105 cites W4283732315 @default.
- W4386231105 cites W4286361941 @default.
- W4386231105 cites W4308310215 @default.
- W4386231105 cites W4313267411 @default.
- W4386231105 doi "https://doi.org/10.1109/lsp.2023.3309153" @default.
- W4386231105 hasPublicationYear "2023" @default.
- W4386231105 type Work @default.
- W4386231105 citedByCount "0" @default.
- W4386231105 crossrefType "journal-article" @default.
- W4386231105 hasAuthorship W4386231105A5018866860 @default.
- W4386231105 hasAuthorship W4386231105A5019018136 @default.
- W4386231105 hasAuthorship W4386231105A5045137258 @default.
- W4386231105 hasConcept C104663316 @default.
- W4386231105 hasConcept C115961682 @default.
- W4386231105 hasConcept C121332964 @default.
- W4386231105 hasConcept C138885662 @default.
- W4386231105 hasConcept C141353440 @default.
- W4386231105 hasConcept C153180895 @default.
- W4386231105 hasConcept C154945302 @default.
- W4386231105 hasConcept C158525013 @default.
- W4386231105 hasConcept C192562407 @default.
- W4386231105 hasConcept C2776151529 @default.
- W4386231105 hasConcept C2776401178 @default.
- W4386231105 hasConcept C2778755073 @default.
- W4386231105 hasConcept C2778971668 @default.
- W4386231105 hasConcept C31972630 @default.
- W4386231105 hasConcept C41008148 @default.
- W4386231105 hasConcept C41895202 @default.
- W4386231105 hasConcept C45347329 @default.
- W4386231105 hasConcept C49040817 @default.
- W4386231105 hasConcept C50644808 @default.
- W4386231105 hasConcept C62520636 @default.
- W4386231105 hasConcept C69744172 @default.
- W4386231105 hasConceptScore W4386231105C104663316 @default.
- W4386231105 hasConceptScore W4386231105C115961682 @default.
- W4386231105 hasConceptScore W4386231105C121332964 @default.
- W4386231105 hasConceptScore W4386231105C138885662 @default.
- W4386231105 hasConceptScore W4386231105C141353440 @default.
- W4386231105 hasConceptScore W4386231105C153180895 @default.
- W4386231105 hasConceptScore W4386231105C154945302 @default.
- W4386231105 hasConceptScore W4386231105C158525013 @default.
- W4386231105 hasConceptScore W4386231105C192562407 @default.
- W4386231105 hasConceptScore W4386231105C2776151529 @default.
- W4386231105 hasConceptScore W4386231105C2776401178 @default.
- W4386231105 hasConceptScore W4386231105C2778755073 @default.
- W4386231105 hasConceptScore W4386231105C2778971668 @default.
- W4386231105 hasConceptScore W4386231105C31972630 @default.
- W4386231105 hasConceptScore W4386231105C41008148 @default.
- W4386231105 hasConceptScore W4386231105C41895202 @default.
- W4386231105 hasConceptScore W4386231105C45347329 @default.
- W4386231105 hasConceptScore W4386231105C49040817 @default.
- W4386231105 hasConceptScore W4386231105C50644808 @default.
- W4386231105 hasConceptScore W4386231105C62520636 @default.
- W4386231105 hasConceptScore W4386231105C69744172 @default.
- W4386231105 hasLocation W43862311051 @default.
- W4386231105 hasOpenAccess W4386231105 @default.
- W4386231105 hasPrimaryLocation W43862311051 @default.