{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T17:06:51Z","timestamp":1772644011017,"version":"3.50.1"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"Research Project of Beijing Municipal Natural Science Foundation","award":["No.BJXZ2021-012-00046"],"award-info":[{"award-number":["No.BJXZ2021-012-00046"]}]},{"name":"Research Project of Beijing Municipal Natural Science Foundation","award":["No.BJXZ2021-012-00046"],"award-info":[{"award-number":["No.BJXZ2021-012-00046"]}]},{"name":"Research Project of Beijing Municipal Natural Science Foundation","award":["No.BJXZ2021-012-00046"],"award-info":[{"award-number":["No.BJXZ2021-012-00046"]}]},{"name":"Research Project of Beijing Municipal Natural Science Foundation","award":["No.BJXZ2021-012-00046"],"award-info":[{"award-number":["No.BJXZ2021-012-00046"]}]},{"name":"Research Project of Beijing Municipal Natural Science Foundation","award":["No.BJXZ2021-012-00046"],"award-info":[{"award-number":["No.BJXZ2021-012-00046"]}]},{"name":"Research Project of Beijing Municipal Natural Science Foundation","award":["No.BJXZ2021-012-00046"],"award-info":[{"award-number":["No.BJXZ2021-012-00046"]}]},{"name":"Research Project of Beijing Municipal Natural Science Foundation","award":["No.BJXZ2021-012-00046"],"award-info":[{"award-number":["No.BJXZ2021-012-00046"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2026,1]]},"DOI":"10.1007\/s00371-025-04214-y","type":"journal-article","created":{"date-parts":[[2026,1,12]],"date-time":"2026-01-12T10:03:04Z","timestamp":1768212184000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Enhanced infrared and visible image fusion via correlation-driven rules and parameter-free attention mechanism"],"prefix":"10.1007","volume":"42","author":[{"given":"Hongtian","family":"Shan","sequence":"first","affiliation":[]},{"given":"Yifan","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Xitian","family":"Lu","sequence":"additional","affiliation":[]},{"given":"Jiangrong","family":"Lin","sequence":"additional","affiliation":[]},{"given":"Lei","family":"Deng","sequence":"additional","affiliation":[]},{"given":"Mingli","family":"Dong","sequence":"additional","affiliation":[]},{"given":"Lianqing","family":"Zhu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2026,1,12]]},"reference":[{"issue":"12","key":"4214_CR1","doi-asserted-by":"publisher","first-page":"1890","DOI":"10.1016\/j.aeue.2015.09.004","volume":"69","author":"V Aslantas","year":"2015","unstructured":"Aslantas, V., Bendes, E.: A new image quality metric for image fusion: the sum of the correlations of differences. Aeu-Int. J. Electr. Commun. 69(12), 1890\u20131896 (2015)","journal-title":"Aeu-Int. J. Electr. Commun."},{"key":"4214_CR2","doi-asserted-by":"publisher","first-page":"52","DOI":"10.1016\/j.infrared.2016.01.009","volume":"76","author":"DP Bavirisetti","year":"2016","unstructured":"Bavirisetti, D.P., Dhuli, R.: Two-scale image fusion of visible and infrared images using saliency detection. Infrared Phys. Technol. 76, 52\u201364 (2016)","journal-title":"Infrared Phys. Technol."},{"key":"4214_CR3","doi-asserted-by":"crossref","unstructured":"Bavirisetti, D.P., Xiao, G., Liu, G.: Multi-sensor image fusion based on fourth order partial differential equations. In: 2017 20th International Conference on Information Fusion (Fusion), IEEE, pp 1\u20139, (2017)","DOI":"10.23919\/ICIF.2017.8009719"},{"key":"4214_CR4","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1016\/j.optcom.2014.12.032","volume":"341","author":"G Cui","year":"2015","unstructured":"Cui, G., Feng, H., Xu, Z., et al.: Detail preserved fusion of visible and infrared images using regional saliency extraction and multi-scale image decomposition. Opt. Commun. 341, 199\u2013209 (2015)","journal-title":"Opt. Commun."},{"issue":"12","key":"4214_CR5","doi-asserted-by":"publisher","first-page":"2959","DOI":"10.1109\/26.477498","volume":"43","author":"AM Eskicioglu","year":"1995","unstructured":"Eskicioglu, A.M., Fisher, P.S.: Image quality measures and their performance. IEEE Trans. Commun. 43(12), 2959\u20132965 (1995)","journal-title":"IEEE Trans. Commun."},{"issue":"2","key":"4214_CR6","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/j.inffus.2011.08.002","volume":"14","author":"Y Han","year":"2013","unstructured":"Han, Y., Cai, Y., Cao, Y., et al.: A new image fusion performance metric based on visual information fidelity. Inform. fusion 14(2), 127\u2013135 (2013)","journal-title":"Inform. fusion"},{"key":"4214_CR7","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1016\/j.aqpro.2015.02.019","volume":"4","author":"P Jagalingam","year":"2015","unstructured":"Jagalingam, P., Hegde, A.V.: A review of quality metrics for fused image. Aquatic Proce. 4, 133\u2013142 (2015)","journal-title":"Aquatic Proce."},{"key":"4214_CR8","doi-asserted-by":"crossref","unstructured":"Jia, X., Zhu, C., Li, M., et al.: Llvip: a visible-infrared paired dataset for low-light vision. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp 3496\u20133504 (2021)","DOI":"10.1109\/ICCVW54120.2021.00389"},{"key":"4214_CR9","doi-asserted-by":"publisher","first-page":"2226","DOI":"10.1109\/TMM.2022.3144890","volume":"25","author":"N Jiang","year":"2023","unstructured":"Jiang, N., Sheng, B., Li, P., et al.: Photohelper: portrait photographing guidance via deep feature retrieval and fusion. IEEE Trans. Multimedia 25, 2226\u20132238 (2023)","journal-title":"IEEE Trans. Multimedia"},{"key":"4214_CR10","doi-asserted-by":"publisher","first-page":"478","DOI":"10.1016\/j.infrared.2017.07.010","volume":"85","author":"X Jin","year":"2017","unstructured":"Jin, X., Jiang, Q., Yao, S., et al.: A survey of infrared and visual image fusion methods. Infrared Phys. Technol. 85, 478\u2013501 (2017)","journal-title":"Infrared Phys. Technol."},{"key":"4214_CR11","doi-asserted-by":"publisher","first-page":"3845","DOI":"10.1109\/TIP.2020.2966075","volume":"29","author":"H Jung","year":"2020","unstructured":"Jung, H., Kim, Y., Jang, H., et al.: Unsupervised deep image fusion with structure tensor representations. IEEE Trans. Image Process. 29, 3845\u20133858 (2020)","journal-title":"IEEE Trans. Image Process."},{"issue":"5","key":"4214_CR12","doi-asserted-by":"publisher","first-page":"2614","DOI":"10.1109\/TIP.2018.2887342","volume":"28","author":"H Li","year":"2019","unstructured":"Li, H., Wu, X.J.: Densefuse: a fusion approach to infrared and visible images. IEEE Trans. Image Process. 28(5), 2614\u20132623 (2019)","journal-title":"IEEE Trans. Image Process."},{"key":"4214_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2023.102147","volume":"103","author":"H Li","year":"2024","unstructured":"Li, H., Wu, X.J.: CrossFuse: a novel cross attention mechanism based infrared and visible image fusion approach. Inform. Fusion 103, 102147 (2024)","journal-title":"Inform. Fusion"},{"key":"4214_CR14","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1016\/j.infrared.2016.02.005","volume":"76","author":"H Li","year":"2016","unstructured":"Li, H., Qiu, H., Yu, Z., et al.: Infrared and visible image fusion scheme based on nsct and low-level visual features. Infrared Phys. Technol. 76, 174\u2013184 (2016)","journal-title":"Infrared Phys. Technol."},{"key":"4214_CR15","doi-asserted-by":"crossref","unstructured":"Li, H., Wu, X.J., Kittler, J.: Infrared and visible image fusion using a deep learning framework. In: 2018 24th International Conference on Pattern Recognition (ICPR), IEEE, pp 2705\u20132710, (2018)","DOI":"10.1109\/ICPR.2018.8546006"},{"key":"4214_CR16","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1016\/j.inffus.2021.02.023","volume":"73","author":"H Li","year":"2021","unstructured":"Li, H., Wu, X.J., Kittler, J.: Rfn-nest: an end-to-end residual fusion network for infrared and visible images. Inform. Fusion 73, 72\u201386 (2021)","journal-title":"Inform. Fusion"},{"issue":"10","key":"4214_CR17","doi-asserted-by":"publisher","first-page":"7817","DOI":"10.1007\/s00371-025-03840-w","volume":"41","author":"H Li","year":"2025","unstructured":"Li, H., Wu, S., Deng, L., et al.: Enhancing infrared and visible image fusion through multiscale gaussian total variation and adaptive local entropy. Visual Comput. 41(10), 7817\u20137838 (2025)","journal-title":"Visual Comput."},{"key":"4214_CR18","doi-asserted-by":"crossref","unstructured":"Liu, J., Fan, X., Huang, Z., et al.: Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition, pp 5802\u20135811, (2022)","DOI":"10.1109\/CVPR52688.2022.00571"},{"key":"4214_CR19","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.inffus.2016.02.001","volume":"31","author":"J Ma","year":"2016","unstructured":"Ma, J., Chen, C., Li, C., et al.: Infrared and visible image fusion via gradient transfer and total variation minimization. Inform. Fusion 31, 100\u2013109 (2016)","journal-title":"Inform. Fusion"},{"key":"4214_CR20","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.inffus.2018.02.004","volume":"45","author":"J Ma","year":"2019","unstructured":"Ma, J., Ma, Y., Li, C.: Infrared and visible image fusion methods and applications: a survey. Inform. Fusion 45, 153\u2013178 (2019)","journal-title":"Inform. Fusion"},{"key":"4214_CR21","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1016\/j.inffus.2018.09.004","volume":"48","author":"J Ma","year":"2019","unstructured":"Ma, J., Yu, W., Liang, P., et al.: Fusiongan: a generative adversarial network for infrared and visible image fusion. Inform. Fusion 48, 11\u201326 (2019)","journal-title":"Inform. Fusion"},{"key":"4214_CR22","first-page":"1","volume":"70","author":"J Ma","year":"2021","unstructured":"Ma, J., Tang, L., Xu, M., et al.: Stdfusionnet: an infrared and visible image fusion network based on salient target detection. IEEE Trans. Instrum. Meas. 70, 1\u201313 (2021)","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"7","key":"4214_CR23","doi-asserted-by":"publisher","first-page":"1200","DOI":"10.1109\/JAS.2022.105686","volume":"9","author":"J Ma","year":"2022","unstructured":"Ma, J., Tang, L., Fan, F., et al.: Swinfusion: cross-domain long-range learning for general image fusion via swin transformer. IEEE\/CAA J. Autom. Sinica 9(7), 1200\u20131217 (2022)","journal-title":"IEEE\/CAA J. Autom. Sinica"},{"issue":"2","key":"4214_CR24","doi-asserted-by":"publisher","first-page":"599","DOI":"10.3390\/s23020599","volume":"23","author":"W Ma","year":"2023","unstructured":"Ma, W., Wang, K., Li, J., et al.: Infrared and visible image fusion technology and application: a review. Sensors 23(2), 599 (2023)","journal-title":"Sensors"},{"key":"4214_CR25","doi-asserted-by":"crossref","unstructured":"Meng, Z., Li, H., Zhang, Z., et al.: Comofusion: fast and high-quality fusion of infrared and visible image with consistency model. In: Chinese Conference on Pattern Recognition and Computer Vision (PRCV), Springer, pp 539\u2013553, (2024)","DOI":"10.1007\/978-981-97-8685-5_38"},{"issue":"2","key":"4214_CR26","doi-asserted-by":"publisher","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., et al.: Remote sensing image fusion using the curvelet transform. Inform. Fusion 8(2), 143\u2013156 (2007)","journal-title":"Inform. Fusion"},{"issue":"1","key":"4214_CR27","doi-asserted-by":"publisher","DOI":"10.1117\/1.2945910","volume":"2","author":"JW Roberts","year":"2008","unstructured":"Roberts, J.W., Van Aardt, J.A., Ahmed, F.B.: Assessment of image fusion procedures using entropy, image quality, and multispectral classification. J. Appl. Remote Sens. 2(1), 023522 (2008)","journal-title":"J. Appl. Remote Sens."},{"key":"4214_CR28","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1016\/j.inffus.2021.12.004","volume":"82","author":"L Tang","year":"2022","unstructured":"Tang, L., Yuan, J., Ma, J.: Image fusion in the loop of high-level vision tasks: a semantic-aware real-time infrared and visible image fusion network. Inform. Fusion 82, 28\u201342 (2022)","journal-title":"Inform. Fusion"},{"key":"4214_CR29","doi-asserted-by":"publisher","first-page":"79","DOI":"10.1016\/j.inffus.2022.03.007","volume":"83","author":"L Tang","year":"2022","unstructured":"Tang, L., Yuan, J., Zhang, H., et al.: Piafusion: a progressive infrared and visible image fusion network based on illumination aware. Inform. Fusion 83, 79\u201392 (2022)","journal-title":"Inform. Fusion"},{"key":"4214_CR30","doi-asserted-by":"crossref","unstructured":"Tang, W., He, F., Liu, Y., et al.: Datfuse: infrared and visible image fusion via dual attention transformer. In: IEEE Transactions on Circuits and Systems for Video Technology (2023)","DOI":"10.1109\/TCSVT.2023.3234340"},{"key":"4214_CR31","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1016\/j.dib.2017.09.038","volume":"15","author":"A Toet","year":"2017","unstructured":"Toet, A.: The tno multiband image data collection. Data Brief 15, 249\u2013251 (2017)","journal-title":"Data Brief"},{"issue":"7","key":"4214_CR32","doi-asserted-by":"publisher","first-page":"1879","DOI":"10.1016\/j.sigpro.2012.11.022","volume":"93","author":"H Wang","year":"2013","unstructured":"Wang, H., Yang, Q., Li, R.: Tunable-q contourlet-based multi-sensor image fusion. Signal Process. 93(7), 1879\u20131891 (2013)","journal-title":"Signal Process."},{"issue":"1","key":"4214_CR33","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s00371-023-02768-3","volume":"40","author":"S Wang","year":"2023","unstructured":"Wang, S., Sun, Z., Li, Q.: High-to-low-level feature matching and complementary information fusion for reference-based image super-resolution. Vis Comput. 40(1), 99\u2013108 (2023)","journal-title":"Vis Comput."},{"key":"4214_CR34","first-page":"1","volume":"63","author":"S Wang","year":"2025","unstructured":"Wang, S., Yang, X., Lu, R., et al.: Mrod-yolo: multimodal joint representation for small object detection in remote sensing imagery via multiscale iterative aggregation. IEEE Trans. Geosci. Remote Sens. 63, 1\u201314 (2025)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"4214_CR35","doi-asserted-by":"crossref","unstructured":"Wen, Y., Luo, B., Shi, W., et al.: Sat-net: Structure-aware transformer-based attention fusion network for low-quality retinal fundus images enhancement. In: IEEE Transactions on Multimedia pp 1\u201314 (2025)","DOI":"10.1109\/TMM.2025.3565935"},{"issue":"1","key":"4214_CR36","doi-asserted-by":"publisher","first-page":"502","DOI":"10.1109\/TPAMI.2020.3012548","volume":"44","author":"H Xu","year":"2020","unstructured":"Xu, H., Ma, J., Jiang, J., et al.: U2fusion: a unified unsupervised image fusion network. IEEE Trans. Pattern Anal. Mach. Intell. 44(1), 502\u2013518 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"4214_CR37","doi-asserted-by":"crossref","unstructured":"Xu, Q., Long, C., Yu, L., et al.: Road extraction with satellite images and partial road maps. IEEE Trans. Geosci. Remote Sens. 61, 1\u201314 (2023)","DOI":"10.1109\/TGRS.2023.3261332"},{"issue":"2","key":"4214_CR38","first-page":"57","volume":"28","author":"L Zhan","year":"2017","unstructured":"Zhan, L., Zhuang, Y., Huang, L.: Infrared and visible images fusion method based on discrete wavelet transform. J. Comput. 28(2), 57\u201371 (2017)","journal-title":"J. Comput."},{"key":"4214_CR39","doi-asserted-by":"crossref","unstructured":"Zhang, M., Tian, X.: Transformer architecture based on mutual attention for image-anomaly detection. Virtual Reality Intell. Hardware 5(1), 57\u201367 (2023)","DOI":"10.1016\/j.vrih.2022.07.006"},{"key":"4214_CR40","first-page":"1","volume":"74","author":"T Zhang","year":"2025","unstructured":"Zhang, T., Yang, X., Lu, R., et al.: Modal feature disentanglement and contribution estimation for multimodality image fusion. IEEE Trans. Instrum. Meas. 74, 1\u201316 (2025)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"4214_CR41","doi-asserted-by":"publisher","first-page":"227","DOI":"10.1016\/j.infrared.2017.05.007","volume":"83","author":"Y Zhang","year":"2017","unstructured":"Zhang, Y., Zhang, L., Bai, X., et al.: Infrared and visual image fusion through infrared feature extraction and visual information preservation. Infrared Phys. Technol. 83, 227\u2013237 (2017)","journal-title":"Infrared Phys. Technol."},{"key":"4214_CR42","doi-asserted-by":"publisher","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., et al.: Ifcnn: a general image fusion framework based on convolutional neural network. Inform. Fusion 54, 99\u2013118 (2020)","journal-title":"Inform. Fusion"},{"key":"4214_CR43","doi-asserted-by":"publisher","first-page":"138","DOI":"10.1016\/j.inffus.2015.06.003","volume":"27","author":"W Zhao","year":"2016","unstructured":"Zhao, W., Xu, Z., Zhao, J.: Gradient entropy metric and p-laplace diffusion constraint-based algorithm for noisy multispectral image fusion. Inform. Fusion 27, 138\u2013149 (2016)","journal-title":"Inform. Fusion"},{"issue":"1","key":"4214_CR44","doi-asserted-by":"publisher","DOI":"10.1002\/cav.2201","volume":"35","author":"X Zhu","year":"2024","unstructured":"Zhu, X., Yao, X., Zhang, J., et al.: Tmsdnet: transformer with multi-scale dense network for single and multi-view 3d reconstruction. Comput. Animation Virtual Worlds 35(1), e2201 (2024)","journal-title":"Comput. Animation Virtual Worlds"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-025-04214-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-025-04214-y","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-025-04214-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T13:03:06Z","timestamp":1772629386000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-025-04214-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1]]},"references-count":44,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,1]]}},"alternative-id":["4214"],"URL":"https:\/\/doi.org\/10.1007\/s00371-025-04214-y","relation":{"has-preprint":[{"id-type":"doi","id":"10.21203\/rs.3.rs-7227512\/v1","asserted-by":"object"}]},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"value":"0178-2789","type":"print"},{"value":"1432-2315","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1]]},"assertion":[{"value":"27 July 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"14 November 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"12 January 2026","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"124"}}