{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T12:10:03Z","timestamp":1779451803877,"version":"3.53.1"},"reference-count":34,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T00:00:00Z","timestamp":1777593600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/100007219","name":"Shanghai Municipal Natural Science Foundation","doi-asserted-by":"publisher","award":["22ZR1416500"],"award-info":[{"award-number":["22ZR1416500"]}],"id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2024YFC3307700"],"award-info":[{"award-number":["2024YFC3307700"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2026,5]]},"DOI":"10.1016\/j.knosys.2026.115853","type":"journal-article","created":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T23:50:11Z","timestamp":1774396211000},"page":"115853","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Multi-focus image fusion based on multi-scale feature extraction and edge preservation techniques"],"prefix":"10.1016","volume":"341","author":[{"ORCID":"https:\/\/orcid.org\/0009-0005-7481-4458","authenticated-orcid":false,"given":"Baojun","family":"Zhao","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7062-4404","authenticated-orcid":false,"given":"Fei","family":"Luo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4446-227X","authenticated-orcid":false,"given":"Luis Rojas","family":"Pino","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8892-3760","authenticated-orcid":false,"given":"Weichao","family":"Ding","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7020-1033","authenticated-orcid":false,"given":"Xueqin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"78","reference":[{"issue":"3","key":"10.1016\/j.knosys.2026.115853_bib0001","doi-asserted-by":"crossref","first-page":"863","DOI":"10.3390\/s21030863","article-title":"Fast multi-focus fusion based on deep learning for early-stage embryo image enhancement","volume":"21","author":"Raudonis","year":"2021","journal-title":"Sensors"},{"issue":"9","key":"10.1016\/j.knosys.2026.115853_bib0002","first-page":"4819","article-title":"Deep learning-based multi-focus image fusion: a survey and a comparative study","volume":"44","author":"Zhang","year":"2021","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.knosys.2026.115853_bib0003","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.inffus.2022.06.001","article-title":"Multi-focus image fusion with deep residual learning and focus property detection","volume":"86","author":"Liu","year":"2022","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.115853_bib0004","doi-asserted-by":"crossref","first-page":"8668","DOI":"10.1109\/TIP.2020.3018261","article-title":"An \u03b1-matte boundary defocus model-based cascaded network for multi-focus image fusion","volume":"29","author":"Ma","year":"2020","journal-title":"IEEE Trans. Image Process."},{"issue":"9","key":"10.1016\/j.knosys.2026.115853_bib0005","doi-asserted-by":"crossref","DOI":"10.1016\/j.jksuci.2023.101751","article-title":"AFCANet: An adaptive feature concatenate attention network for multi-focus image fusion","volume":"35","author":"Liu","year":"2023","journal-title":"J. King Saud Univ. Comput. Inf. Sci."},{"key":"10.1016\/j.knosys.2026.115853_bib0006","doi-asserted-by":"crossref","DOI":"10.1016\/j.eswa.2023.121156","article-title":"Combining transformers with CNN for multi-focus image fusion","volume":"235","author":"Duan","year":"2024","journal-title":"Expert Syst. Appl."},{"issue":"10","key":"10.1016\/j.knosys.2026.115853_bib0007","doi-asserted-by":"crossref","first-page":"2529","DOI":"10.1007\/s11263-023-01806-w","article-title":"When multi-focus image fusion networks meet traditional edge-preservation technology","volume":"131","author":"Wang","year":"2023","journal-title":"Int. J. Comput. Vis."},{"key":"10.1016\/j.knosys.2026.115853_bib0008","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.inffus.2016.12.001","article-title":"Multi-focus image fusion with a deep convolutional neural network","volume":"36","author":"Liu","year":"2017","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.115853_bib0009","doi-asserted-by":"crossref","first-page":"4816","DOI":"10.1109\/TIP.2020.2976190","article-title":"DRPL: deep regression pair learning for multi-focus image fusion","volume":"29","author":"Li","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.knosys.2026.115853_bib0010","doi-asserted-by":"crossref","first-page":"5793","DOI":"10.1007\/s00521-020-05358-9","article-title":"SESF-fuse: an unsupervised deep model for multi-focus image fusion","volume":"33","author":"Ma","year":"2021","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.knosys.2026.115853_bib0011","doi-asserted-by":"crossref","first-page":"26316","DOI":"10.1109\/ACCESS.2020.2971137","article-title":"A deep model for multi-focus image fusion based on gradients and connected regions","volume":"8","author":"Xu","year":"2020","journal-title":"IEEE Access"},{"issue":"3","key":"10.1016\/j.knosys.2026.115853_bib0012","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1049\/ipr2.12668","article-title":"An unsupervised multi-focus image fusion method based on transformer and U-Net","volume":"17","author":"Jin","year":"2023","journal-title":"IET Image Proc."},{"key":"10.1016\/j.knosys.2026.115853_bib0013","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2025.129984","article-title":"LSKN-MFIF: large selective kernel network for multi-focus image fusion","volume":"635","author":"Zhai","year":"2025","journal-title":"Neurocomputing"},{"issue":"6","key":"10.1016\/j.knosys.2026.115853_bib0014","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1109\/TPAMI.2002.1008390","article-title":"Fundamental relationship between bilateral filtering, adaptive smoothing, and the nonlinear diffusion equation","volume":"24","author":"Barash","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.knosys.2026.115853_bib0015","series-title":"ACM SIGGRAPH 2011 Papers","first-page":"1","article-title":"Domain transform for edge-aware image and video processing","author":"Gastal","year":"2011"},{"key":"10.1016\/j.knosys.2026.115853_bib0016","series-title":"Proceedings of the European Conference on Computer Vision (ECCV)","first-page":"3","article-title":"CBAM: convolutional block attention module","author":"Woo","year":"2018"},{"issue":"6","key":"10.1016\/j.knosys.2026.115853_bib0017","first-page":"6180","article-title":"WaveFormer: wavelet transformer for noise-robust video inpainting","volume":"38","author":"Wu","year":"2024","journal-title":"Proc. AAAI Conf. Artif. Intell."},{"key":"10.1016\/j.knosys.2026.115853_bib0018","doi-asserted-by":"crossref","unstructured":"Z. Wu, K. Chen, K. Li, H. Fan, Y. Yang, BVINet: unlocking blind video inpainting with zero annotations, arXiv preprint, (2025), https:\/\/arxiv.org\/abs\/2502.01181.","DOI":"10.1109\/ICCV51701.2025.01301"},{"key":"10.1016\/j.knosys.2026.115853_bib0019","series-title":"Computer Vision\u2013ECCV 2014: 13th European Conference, Zurich, Switzerland, September 6\u201312, 2014, Proceedings, Part v 13","first-page":"740","article-title":"Microsoft COCO: common objects in context","author":"Lin","year":"2014"},{"key":"10.1016\/j.knosys.2026.115853_bib0020","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.inffus.2014.10.004","article-title":"Multi-focus image fusion using dictionary-based sparse representation","volume":"25","author":"Nejati","year":"2015","journal-title":"Inf. fusion"},{"issue":"2","key":"10.1016\/j.knosys.2026.115853_bib0021","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.inffus.2006.02.001","article-title":"Remote sensing image fusion using the curvelet transform","volume":"8","author":"Nencini","year":"2007","journal-title":"Inf. fusion"},{"key":"10.1016\/j.knosys.2026.115853_bib0022","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.inffus.2014.05.004","article-title":"Multi-focus image fusion with dense SIFT","volume":"23","author":"Liu","year":"2015","journal-title":"Inf. Fusion"},{"issue":"3","key":"10.1016\/j.knosys.2026.115853_bib0023","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1006\/gmip.1995.1022","article-title":"Multisensor image fusion using the wavelet transform","volume":"57","author":"Li","year":"1995","journal-title":"Graphical Models Image Process."},{"issue":"7","key":"10.1016\/j.knosys.2026.115853_bib0024","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1109\/JAS.2022.105686","article-title":"SwinFusion: cross-domain long-range learning for general image fusion via swin transformer","volume":"9","author":"Ma","year":"2022","journal-title":"IEEE\/CAA J. Autom. Sin."},{"issue":"1","key":"10.1016\/j.knosys.2026.115853_bib0025","doi-asserted-by":"crossref","first-page":"502","DOI":"10.1109\/TPAMI.2020.3012548","article-title":"U2Fusion: a unified unsupervised image fusion network","volume":"44","author":"Xu","year":"2020","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"10.1016\/j.knosys.2026.115853_bib0026","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.inffus.2022.11.010","article-title":"MUFusion: a general unsupervised image fusion network based on memory unit","volume":"92","author":"Cheng","year":"2023","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.knosys.2026.115853_bib0027","doi-asserted-by":"crossref","DOI":"10.1016\/j.compeleceng.2025.110238","article-title":"Multi-focus image fusion with visual state space model and dual adversarial learning","volume":"123","author":"Xie","year":"2025","journal-title":"Comput. Electr. Eng."},{"issue":"18","key":"10.1016\/j.knosys.2026.115853_bib0028","doi-asserted-by":"crossref","first-page":"1066","DOI":"10.1049\/el:20081754","article-title":"Comments on \u2019information measure for performance of image fusion\u2019","volume":"44","author":"Hossny","year":"2008","journal-title":"Electron. Lett."},{"issue":"11","key":"10.1016\/j.knosys.2026.115853_bib0029","doi-asserted-by":"crossref","first-page":"626","DOI":"10.1049\/el:20060693","article-title":"Image fusion metric based on mutual information and Tsallis entropy","volume":"42","author":"Cvejic","year":"2006","journal-title":"Electron. Lett."},{"key":"10.1016\/j.knosys.2026.115853_bib0030","doi-asserted-by":"crossref","first-page":"469","DOI":"10.1016\/B978-0-12-372529-5.00017-2","article-title":"Performance evaluation of image fusion techniques","volume":"19","author":"Wang","year":"2008","journal-title":"Image Fusion Algorithms Appl."},{"issue":"4","key":"10.1016\/j.knosys.2026.115853_bib0031","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1049\/el:20000267","article-title":"Objective image fusion performance measure","volume":"36","author":"Xydeas","year":"2000","journal-title":"Electron. Lett."},{"key":"10.1016\/j.knosys.2026.115853_bib0032","series-title":"2008 9th International Conference on Signal Processing","first-page":"965","article-title":"A novel image fusion metric based on multi-scale analysis","author":"Wang","year":"2008"},{"issue":"2","key":"10.1016\/j.knosys.2026.115853_bib0033","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/j.inffus.2006.09.001","article-title":"A novel similarity based quality metric for image fusion","volume":"9","author":"Yang","year":"2008","journal-title":"Inf. Fusion"},{"issue":"10","key":"10.1016\/j.knosys.2026.115853_bib0034","doi-asserted-by":"crossref","first-page":"1421","DOI":"10.1016\/j.imavis.2007.12.002","article-title":"A new automated quality assessment algorithm for image fusion","volume":"27","author":"Chen","year":"2009","journal-title":"Image Vis. Comput."}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126005794?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705126005794?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,22]],"date-time":"2026-05-22T11:42:30Z","timestamp":1779450150000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705126005794"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,5]]},"references-count":34,"alternative-id":["S0950705126005794"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2026.115853","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2026,5]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Multi-focus image fusion based on multi-scale feature extraction and edge preservation techniques","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2026.115853","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115853"}}