{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,11]],"date-time":"2026-01-11T07:23:40Z","timestamp":1768116220461,"version":"3.49.0"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T00:00:00Z","timestamp":1690761600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T00:00:00Z","timestamp":1690761600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61772319"],"award-info":[{"award-number":["61772319"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62002200"],"award-info":[{"award-number":["62002200"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61976125ff 61976124"],"award-info":[{"award-number":["61976125ff 61976124"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"DOI":"10.1007\/s11042-023-15342-9","type":"journal-article","created":{"date-parts":[[2023,7,31]],"date-time":"2023-07-31T15:04:42Z","timestamp":1690815882000},"page":"20055-20082","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["SFPN: segmentation-based feature pyramid network for multi-focus image fusion"],"prefix":"10.1007","volume":"83","author":[{"given":"Pan","family":"Wu","sequence":"first","affiliation":[]},{"given":"Limai","family":"Jiang","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6511-6704","authenticated-orcid":false,"given":"Ying","family":"Li","sequence":"additional","affiliation":[]},{"given":"Hui","family":"Fan","sequence":"additional","affiliation":[]},{"given":"Jinjiang","family":"Li","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,7,31]]},"reference":[{"key":"15342_CR1","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/j.inffus.2019.02.003","volume":"51","author":"M Amin-Naji","year":"2019","unstructured":"Amin-Naji M, Aghagolzadeh A, Ezoji M (2019) Ensemble of cnn for multi-focus image fusion. Inf Fus 51:201\u2013214","journal-title":"Inf Fus"},{"issue":"12","key":"15342_CR2","doi-asserted-by":"crossref","first-page":"8861","DOI":"10.1016\/j.eswa.2010.06.011","volume":"37","author":"V Aslantas","year":"2010","unstructured":"Aslantas V, Kurban R (2010) Fusion of multi-focus images using differential evolution algorithm. Exp Syst Appl 37(12):8861\u20138870","journal-title":"Exp Syst Appl"},{"issue":"19","key":"15342_CR3","doi-asserted-by":"crossref","first-page":"13311","DOI":"10.1007\/s11042-020-08670-7","volume":"79","author":"S Aymaz","year":"2020","unstructured":"Aymaz S, K\u00f6se C, Aymaz S\u0307 (2020) Multi-focus image fusion for different datasets with super-resolution using gradient-based new fusion rule. Multimed Tool Appl 79(19):13311\u201313350","journal-title":"Multimed Tool Appl"},{"key":"15342_CR4","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/j.inffus.2014.05.003","volume":"22","author":"X Bai","year":"2015","unstructured":"Bai X, Zhang Y, Zhou F, Xue B (2015) Quadtree-based multi-focus image fusion using a weighted focus-measure. Inf Fus 22:105\u2013118","journal-title":"Inf Fus"},{"key":"15342_CR5","doi-asserted-by":"crossref","unstructured":"Burt PJ, Adelson EH (1987) The laplacian pyramid as a compact image code. In: Readings in computer vision, pp 671\u2013679. Elsevier","DOI":"10.1016\/B978-0-08-051581-6.50065-9"},{"issue":"10","key":"15342_CR6","doi-asserted-by":"crossref","first-page":"1421","DOI":"10.1016\/j.imavis.2007.12.002","volume":"27","author":"Y Chen","year":"2009","unstructured":"Chen Y, Blum RS (2009) A new automated quality assessment algorithm for image fusion. Image Vis Comput 27(10):1421\u20131432","journal-title":"Image Vis Comput"},{"key":"15342_CR7","doi-asserted-by":"crossref","unstructured":"Chen C, Mu S, Xiao W, Ye Z, Wu L, Ju Q (2019) Improving image captioning with conditional generative adversarial nets. In: Proceedings of the AAAI conference on artificial intelligence, vol. 33, pp 8142\u20138150","DOI":"10.1609\/aaai.v33i01.33018142"},{"issue":"2","key":"15342_CR8","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1049\/el:20073460","volume":"43","author":"N Cvejic","year":"2007","unstructured":"Cvejic N, Bull DR, Canagarajah CN (2007) Metric for multimodal image sensor fusion. Electr Lett 43(2):95\u201396","journal-title":"Electr Lett"},{"issue":"2","key":"15342_CR9","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1016\/j.inffus.2012.01.007","volume":"14","author":"I De","year":"2013","unstructured":"De I, Chanda B (2013) Multi-focus image fusion using a morphology-based focus measure in a quad-tree structure. Inf Fus 14(2):136\u2013146","journal-title":"Inf Fus"},{"key":"15342_CR10","unstructured":"Everingham M, Winn J (2011) The pascal visual object classes challenge 2012 (voc2012) development kit. Pattern Analysis, Statistical Modelling and Computational Learning, Tech Rep p 8"},{"issue":"11","key":"15342_CR11","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1145\/3422622","volume":"63","author":"I Goodfellow","year":"2020","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S, Courville A, Bengio Y (2020) Generative adversarial networks. Commun ACM 63(11):139\u2013144","journal-title":"Commun ACM"},{"issue":"8","key":"15342_CR12","doi-asserted-by":"crossref","first-page":"1982","DOI":"10.1109\/TMM.2019.2895292","volume":"21","author":"X Guo","year":"2019","unstructured":"Guo X, Nie R, Cao J, Zhou D, Mei L, Fusegan KH (2019) Learning to fuse multi-focus image via conditional generative adversarial network. IEEE Trans Multimed 21(8):1982\u20131996","journal-title":"IEEE Trans Multimed"},{"issue":"18","key":"15342_CR13","doi-asserted-by":"crossref","first-page":"1066","DOI":"10.1049\/el:20081754","volume":"44","author":"M Hossny","year":"2008","unstructured":"Hossny M, Nahavandi S, Creighton D (2008) Comments on \u2018information measure for performance of image fusion\u2019. Electr Lett 44(18):1066\u20131067","journal-title":"Electr Lett"},{"key":"15342_CR14","doi-asserted-by":"crossref","unstructured":"Hu J, Li S, Sun G (2018) Squeeze-and-excitation networks. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 7132\u20137141","DOI":"10.1109\/CVPR.2018.00745"},{"issue":"4","key":"15342_CR15","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/j.patrec.2006.09.005","volume":"28","author":"W Huang","year":"2007","unstructured":"Huang W, Jing Z (2007) Evaluation of focus measures in multi-focus image fusion. Pattern Recogn Lett 28(4):493\u2013500","journal-title":"Pattern Recogn Lett"},{"key":"15342_CR16","doi-asserted-by":"crossref","unstructured":"Jaritz M, Vu T-H, de Charette R, Wirbel E, P\u00e9rez P (2020) xmuda: Cross-modal unsupervised domain adaptation for 3d semantic segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 12605\u201312614","DOI":"10.1109\/CVPR42600.2020.01262"},{"key":"15342_CR17","doi-asserted-by":"crossref","first-page":"3845","DOI":"10.1109\/TIP.2020.2966075","volume":"29","author":"H Jung","year":"2020","unstructured":"Jung H, Kim Y, Jang H, Ha N, Sohn K (2020) Unsupervised deep image fusion with structure tensor representations. IEEE Trans Image Process 29:3845\u20133858","journal-title":"IEEE Trans Image Process"},{"key":"15342_CR18","doi-asserted-by":"crossref","unstructured":"Lee Y, Park J (2020) Centermask: real-time anchor-free instance segmentation. In: Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition, pp 13906\u201313915","DOI":"10.1109\/CVPR42600.2020.01392"},{"issue":"2","key":"15342_CR19","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1016\/j.inffus.2005.09.006","volume":"8","author":"JJ Lewis","year":"2007","unstructured":"Lewis JJ, O\u2019Callaghan RJ, Nikolov SG, Bull DR, Canagarajah N (2007) Pixel-and region-based image fusion with complex wavelets. Inf Fus 8(2):119\u2013130","journal-title":"Inf Fus"},{"issue":"11","key":"15342_CR20","doi-asserted-by":"crossref","first-page":"4227","DOI":"10.1109\/TCSVT.2021.3049940","volume":"31","author":"J Li","year":"2021","unstructured":"Li J, Feng X, Hua Z (2021) Low-light image enhancement via progressive-recursive network. IEEE Trans Circ Syst Vid Technol 31 (11):4227\u20134240","journal-title":"IEEE Trans Circ Syst Vid Technol"},{"key":"15342_CR21","doi-asserted-by":"crossref","first-page":"4816","DOI":"10.1109\/TIP.2020.2976190","volume":"29","author":"J Li","year":"2020","unstructured":"Li J, Guo X, Lu G, Zhang B, Xu Y, Wu F, Zhang D (2020) Drpl: deep regression pair learning for multi-focus image fusion. IEEE Trans Image Process 29:4816\u20134831","journal-title":"IEEE Trans Image Process"},{"key":"15342_CR22","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.inffus.2016.05.004","volume":"33","author":"S Li","year":"2017","unstructured":"Li S, Kang X, Fang L, Hu J, Yin H (2017) Pixel-level image fusion: a survey of the state of the art. Inf Fus 33:100\u2013112","journal-title":"Inf Fus"},{"issue":"7","key":"15342_CR23","doi-asserted-by":"crossref","first-page":"2864","DOI":"10.1109\/TIP.2013.2244222","volume":"22","author":"S Li","year":"2013","unstructured":"Li S, Kang X, Hu J (2013) Image fusion with guided filtering. IEEE Trans Image Process 22(7):2864\u20132875","journal-title":"IEEE Trans Image Process"},{"issue":"2","key":"15342_CR24","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.inffus.2011.07.001","volume":"14","author":"S Li","year":"2013","unstructured":"Li S, Kang X, Hu J, Yang B (2013) Image matting for fusion of multi-focus images in dynamic scenes. Inf Fus 14(2):147\u2013162","journal-title":"Inf Fus"},{"issue":"3","key":"15342_CR25","doi-asserted-by":"crossref","first-page":"169","DOI":"10.1016\/S1566-2535(01)00038-0","volume":"2","author":"S Li","year":"2001","unstructured":"Li S, Kwok JT, Wang Y (2001) Combination of images with diverse focuses using the spatial frequency. Inf Fus 2(3):169\u2013176","journal-title":"Inf Fus"},{"key":"15342_CR26","doi-asserted-by":"crossref","unstructured":"Li Z, Li J, Zhang F, Fan L (2023) Cadui: cross attention-based depth unfolding iteration network for pan-sharpening remote sensing images. IEEE Trans Geosci Remote Sens","DOI":"10.1109\/TGRS.2023.3267841"},{"issue":"3","key":"15342_CR27","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1006\/gmip.1995.1022","volume":"57","author":"H Li","year":"1995","unstructured":"Li H, Manjunath BS, Mitra SK (1995) Multisensor image fusion using the wavelet transform. Graph Model Image Process 57(3):235\u2013245","journal-title":"Graph Model Image Process"},{"issue":"7","key":"15342_CR28","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1016\/j.imavis.2007.10.012","volume":"26","author":"S Li","year":"2008","unstructured":"Li S, Yang B (2008) Multifocus image fusion using region segmentation and spatial frequency. Image Vis Comput 26(7):971\u2013979","journal-title":"Image Vis Comput"},{"issue":"6","key":"15342_CR29","doi-asserted-by":"crossref","first-page":"1167","DOI":"10.1007\/s00138-013-0502-4","volume":"24","author":"H Li","year":"2013","unstructured":"Li H, Yi C, Li Z (2013) A new fusion scheme for multifocus images based on focused pixels detection. Mach Vis Appl 24(6):1167\u20131181","journal-title":"Mach Vis Appl"},{"key":"15342_CR30","doi-asserted-by":"crossref","unstructured":"Lin T-Y, Doll\u00e1r P, Girshick R, He K, Hariharan B, Belongie S (2017) Feature pyramid networks for object detection. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 2117\u20132125","DOI":"10.1109\/CVPR.2017.106"},{"issue":"1","key":"15342_CR31","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1109\/TPAMI.2011.109","volume":"34","author":"Z Liu","year":"2011","unstructured":"Liu Z, Blasch E, Xue Z, Zhao J, Laganiere R, Wu W (2011) Objective assessment of multiresolution image fusion algorithms for context enhancement in night vision: a comparative study. IEEE Trans Pattern Anal Mach Intell 34 (1):94\u2013109","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"15342_CR32","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.inffus.2014.05.004","volume":"23","author":"Y Liu","year":"2015","unstructured":"Liu Y, Liu S, Wang Z (2015) Multi-focus image fusion with dense sift. Inf Fus 23:139\u2013155","journal-title":"Inf Fus"},{"key":"15342_CR33","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.inffus.2020.06.013","volume":"64","author":"Y Liu","year":"2020","unstructured":"Liu Y, Wang L, Cheng J, Li C, Chen X (2020) Multi-focus image fusion: a survey of the state of the art. Inf Fus 64:71\u201391","journal-title":"Inf Fus"},{"issue":"3","key":"15342_CR34","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1007\/s10489-019-01523-3","volume":"50","author":"T Ma","year":"2020","unstructured":"Ma T, Kuang P, Tian W (2020) An improved recurrent neural networks for 3d object reconstruction. Appl Intell 50(3):905\u2013923","journal-title":"Appl Intell"},{"key":"15342_CR35","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.inffus.2018.09.004","volume":"48","author":"J Ma","year":"2019","unstructured":"Ma J, Wei Y, Liang P, Li C, Fusiongan JJ (2019) A generative adversarial network for infrared and visible image fusion. Inf Fus 48:11\u201326","journal-title":"Inf Fus"},{"key":"15342_CR36","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1016\/j.neucom.2019.01.048","volume":"335","author":"J Ma","year":"2019","unstructured":"Ma J, Zhou Z, Wang B, Miao L, Zong H (2019) Multi-focus image fusion using boosted random walks-based algorithm with two-scale focus maps. Neurocomputing 335:9\u201320","journal-title":"Neurocomputing"},{"key":"15342_CR37","doi-asserted-by":"crossref","unstructured":"Ma B, Zhu Y, Yin X, Ban X, Huang H, Mukeshimana M (2020) Sesf-fuse: an unsupervised deep model for multi-focus image fusion. Neural Comput Appl 1\u201312","DOI":"10.1007\/s00521-020-05358-9"},{"key":"15342_CR38","doi-asserted-by":"crossref","unstructured":"Mao X, Li Q, Xie H, Lau RYK, Wang Z, Smolley SP (2017) Least squares generative adversarial networks. In: Proceedings of the IEEE international conference on computer vision, pp 2794\u20132802","DOI":"10.1109\/ICCV.2017.304"},{"key":"15342_CR39","doi-asserted-by":"crossref","unstructured":"Milletari F, Navab N, Ahmadi S-A (2016) V-net: fully convolutional neural networks for volumetric medical image segmentation. In: 2016 fourth international conference on 3D vision (3DV), IEEE, pp 565\u2013571","DOI":"10.1109\/3DV.2016.79"},{"key":"15342_CR40","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.inffus.2014.10.004","volume":"25","author":"M Nejati","year":"2015","unstructured":"Nejati M, Samavi S, Shirani S (2015) Multi-focus image fusion using dictionary-based sparse representation. Inf Fus 25:72\u201384","journal-title":"Inf Fus"},{"issue":"2","key":"15342_CR41","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.inffus.2006.02.001","volume":"8","author":"F Nencini","year":"2007","unstructured":"Nencini F, Garzelli A, Baronti S, Alparone L (2007) Remote sensing image fusion using the curvelet transform. Inf Fus 8(2):143\u2013156","journal-title":"Inf Fus"},{"key":"15342_CR42","doi-asserted-by":"crossref","unstructured":"Peng C, Zhang X, Gang Y, Luo G, Sun J (2017) Large kernel matters\u2013improve semantic segmentation by global convolutional network. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp 4353\u20134361","DOI":"10.1109\/CVPR.2017.189"},{"key":"15342_CR43","doi-asserted-by":"crossref","unstructured":"Piella G, Heijmans H (2003) A new quality metric for image fusion. In: Proceedings 2003 international conference on image processing (Cat. No. 03 CH37429), vol. 3, IEEE, pp III\u2013173","DOI":"10.1109\/ICIP.2003.1247209"},{"issue":"6","key":"15342_CR44","doi-asserted-by":"crossref","first-page":"1137","DOI":"10.1109\/TPAMI.2016.2577031","volume":"39","author":"S Ren","year":"2016","unstructured":"Ren S, He K, Girshick R, Sun J (2016) Faster r-cnn: towards real-time object detection with region proposal networks. IEEE Trans Pattern Anal Mach Intell 39(6):1137\u20131149","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"15342_CR45","unstructured":"Savi\u0107 S, Babi\u0107 Z (2012) Multifocus image fusion based on empirical mode decomposition. In: 19th IEEE international conference on systems, signals and image processing (IWSSIP)"},{"key":"15342_CR46","first-page":"7","volume":"e654","author":"PN Srinivasu","year":"2021","unstructured":"Srinivasu PN, Balas VE (2021) Self-learning network-based segmentation for real-time brain mr images through haris. PeerJ Comput Sci e654:7","journal-title":"PeerJ Comput Sci"},{"key":"15342_CR47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/978-981-15-5495-7_1","volume":"903","author":"PN Srinivasu","year":"2021","unstructured":"Srinivasu PN, Balas VE, Md Norwawi N (2021) Performance measurement of various hybridized kernels for noise normalization and enhancement in high-resolution mr images. Bio-inspired Neurocomput 903:1\u201324","journal-title":"Bio-inspired Neurocomput"},{"key":"15342_CR48","unstructured":"Stathaki T (2011) Image fusion: algorithms and applications. Elsevier"},{"key":"15342_CR49","first-page":"1","volume":"60","author":"X Su","year":"2022","unstructured":"Su X, Li J, Hua Z (2022) Transformer-based regression network for pansharpening remote sensing images. IEEE Trans Geosci Remote Sens 60:1\u201323","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"15342_CR50","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.ins.2017.12.043","volume":"433","author":"H Tang","year":"2018","unstructured":"Tang H, Xiao B, Li W, Wang G (2018) Pixel convolutional neural network for multi-focus image fusion. Inf Sci 433:125\u2013141","journal-title":"Inf Sci"},{"issue":"4","key":"15342_CR51","doi-asserted-by":"crossref","first-page":"255","DOI":"10.1016\/0167-8655(89)90004-4","volume":"9","author":"A Toet","year":"1989","unstructured":"Toet A (1989) A morphological pyramidal image decomposition. Pattern Recogn Lett 9(4):255\u2013261","journal-title":"Pattern Recogn Lett"},{"issue":"4","key":"15342_CR52","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600\u2013612","journal-title":"IEEE Trans Image Process"},{"key":"15342_CR53","doi-asserted-by":"crossref","unstructured":"Wang P, Chen P, Ye Y, Liu D, Huang Z, Hou X, Cottrell G (2018) Understanding convolution for semantic segmentation. In: 2018 IEEE winter conference on applications of computer vision (WACV), IEEE, pp 1451\u20131460","DOI":"10.1109\/WACV.2018.00163"},{"key":"15342_CR54","unstructured":"Wang P-w, Liu B (2008) A novel image fusion metric based on multi-scale analysis. In: 2008 9th international conference on signal processing, IEEE, pp 965\u2013968"},{"key":"15342_CR55","doi-asserted-by":"crossref","unstructured":"Woo S, Park J, Lee J-Y, Kweon S (2018) Cbam: convolutional block attention module. In: Proceedings of the European conference on computer vision (ECCV), pp 3\u201319","DOI":"10.1007\/978-3-030-01234-2_1"},{"key":"15342_CR56","doi-asserted-by":"crossref","first-page":"1561","DOI":"10.1109\/TCI.2020.3039564","volume":"6","author":"S Xu","year":"2020","unstructured":"Xu S, Ji L, Wang Z, Li P, Sun K, Zhang C, Zhang J (2020) Towards reducing severe defocus spread effects for multi-focus image fusion via an optimization based strategy. IEEE Trans Comput Imag 6:1561\u20131570","journal-title":"IEEE Trans Comput Imag"},{"key":"15342_CR57","unstructured":"Xu H, Ma J, Jiang J, Guo X, Ling H (2020) U2fusion: a unified unsupervised image fusion network. IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"15342_CR58","unstructured":"Xu S, Wei X, Zhang C, Liu J, Zhang J (2020) Mffw: a new dataset for multi-focus image fusion. arXiv:2002.04780"},{"issue":"4","key":"15342_CR59","doi-asserted-by":"crossref","first-page":"308","DOI":"10.1049\/el:20000267","volume":"36","author":"CS Xydeas","year":"2000","unstructured":"Xydeas CS, Petrovic V (2000) Objective image fusion performance measure. Electr Lett 36(4):308\u2013309","journal-title":"Electr Lett"},{"issue":"2","key":"15342_CR60","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1109\/TCI.2018.2889959","volume":"5","author":"Y Yang","year":"2019","unstructured":"Yang Y, Nie Z, Huang S, Lin P, Wu J (2019) Multilevel features convolutional neural network for multifocus image fusion. IEEE Trans Comput Imag 5 (2):262\u2013273","journal-title":"IEEE Trans Comput Imag"},{"issue":"5","key":"15342_CR61","first-page":"2824","volume":"15","author":"Y Yang","year":"2014","unstructured":"Yang Y, Tong S, Huang S, Lin P (2014) Multifocus image fusion based on nsct and focused area detection. IEEE Sensor J 15(5):2824\u20132838","journal-title":"IEEE Sensor J"},{"issue":"19","key":"15342_CR62","doi-asserted-by":"crossref","first-page":"4376","DOI":"10.1016\/j.optcom.2011.05.046","volume":"284","author":"C Yi","year":"2011","unstructured":"Yi C, Li H, Li Z (2011) Multifocus image fusion scheme using focused region detection and multiresolution. Opt Commun 284(19):4376\u20134389","journal-title":"Opt Commun"},{"key":"15342_CR63","doi-asserted-by":"crossref","first-page":"191","DOI":"10.1016\/j.inffus.2016.12.001","volume":"36","author":"L Yu","year":"2017","unstructured":"Yu L, Chen X, Hu P, Wang Z (2017) Multi-focus image fusion with a deep convolutional neural network. Inf Fus 36:191\u2013207","journal-title":"Inf Fus"},{"key":"15342_CR64","unstructured":"Zhang X (2020) Multi-focus image fusion: a benchmark. arXiv:2005.01116"},{"key":"15342_CR65","doi-asserted-by":"crossref","unstructured":"Zhang H, Le Z, Shao Z, Xu H, Mff-gan JM (2021) An unsupervised generative adversarial network with adaptive and gradient joint constraints for multi-focus image fusion. Inf Fus 66:40\u201353","DOI":"10.1016\/j.inffus.2020.08.022"},{"key":"15342_CR66","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.inffus.2019.07.011","volume":"54","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Liu Y, Sun P, Yan H, Zhao X, Li Z (2020) Ifcnn a general image fusion framework based on convolutional neural network. Inf Fus 54:99\u2013118","journal-title":"Inf Fus"},{"key":"15342_CR67","doi-asserted-by":"crossref","unstructured":"Zhang H, Xu H, Xiao Y, Guo X, Ma J (2020) Rethinking the image fusion: a fast unified image fusion network based on proportional maintenance of gradient and intensity. In: Proceedings of the AAAI conference on artificial intelligence, vol. 34, pp 12797\u201312804","DOI":"10.1609\/aaai.v34i07.6975"},{"issue":"4","key":"15342_CR68","doi-asserted-by":"crossref","first-page":"1102","DOI":"10.1109\/TCSVT.2018.2821177","volume":"29","author":"W Zhao","year":"2018","unstructured":"Zhao W, Wang D, Lu H (2018) Multi-focus image fusion with a natural enhancement via a joint multi-level deeply supervised convolutional neural network. IEEE Trans Circ Syst Vid Technol 29(4):1102\u20131115","journal-title":"IEEE Trans Circ Syst Vid Technol"},{"key":"15342_CR69","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.inffus.2013.11.005","volume":"20","author":"Z Zhou","year":"2014","unstructured":"Zhou Z, Li S, Bo W (2014) Multi-scale weighted gradient-based fusion for multi-focus images. Inf Fus 20:60\u201372","journal-title":"Inf Fus"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15342-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-023-15342-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-023-15342-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,15]],"date-time":"2024-02-15T10:32:05Z","timestamp":1707993125000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-023-15342-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,31]]},"references-count":69,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,2]]}},"alternative-id":["15342"],"URL":"https:\/\/doi.org\/10.1007\/s11042-023-15342-9","relation":{},"ISSN":["1573-7721"],"issn-type":[{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,7,31]]},"assertion":[{"value":"15 August 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2023","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 April 2023","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"31 July 2023","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}