{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T02:04:27Z","timestamp":1773972267036,"version":"3.50.1"},"reference-count":65,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T00:00:00Z","timestamp":1775001600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012434","name":"Middle-aged and Young Teachers' Basic Ability Promotion Project of Guangxi","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100012434","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Digital Signal Processing"],"published-print":{"date-parts":[[2026,4]]},"DOI":"10.1016\/j.dsp.2026.105902","type":"journal-article","created":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T16:46:04Z","timestamp":1767977164000},"page":"105902","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["GPF-GAN: An unsupervised generative adversarial network for joint gradient and pixel-constrained fusion of infrared and visible images"],"prefix":"10.1016","volume":"173","author":[{"given":"Pengpeng","family":"Xie","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0009-0005-1947-7102","authenticated-orcid":false,"given":"Ziyang","family":"Ding","sequence":"additional","affiliation":[]},{"given":"Qianfan","family":"Li","sequence":"additional","affiliation":[]},{"given":"Cong","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Shibo","family":"Bin","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.dsp.2026.105902_bib0001","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"5802","article-title":"Target-aware dual adversarial learning and a multi-scenario multi-modality benchmark to fuse infrared and visible for object detection","author":"Liu","year":"2022"},{"key":"10.1016\/j.dsp.2026.105902_bib0002","first-page":"1","article-title":"STDFusionNet: an infrared and visible image fusion network based on salient target detection","volume":"70","author":"Ma","year":"2021","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"4","key":"10.1016\/j.dsp.2026.105902_bib0003","doi-asserted-by":"crossref","first-page":"75","DOI":"10.3390\/chemosensors9040075","article-title":"Visible and near-infrared image acquisition and fusion for night surveillance","volume":"9","author":"Kwon","year":"2021","journal-title":"Chemosensors"},{"key":"10.1016\/j.dsp.2026.105902_bib0004","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.inffus.2019.12.014","article-title":"IVFuseNet: fusion of infrared and visible light images for depth prediction","volume":"58","author":"Li","year":"2020","journal-title":"Inf. Fusion"},{"issue":"4","key":"10.1016\/j.dsp.2026.105902_bib0005","doi-asserted-by":"crossref","first-page":"237","DOI":"10.26599\/JICV.2023.9210018","article-title":"Enhanced target tracking algorithm for autonomous driving based on visible and infrared image fusion","volume":"6","author":"Yuan","year":"2023","journal-title":"J. Intell. Connect. Veh."},{"issue":"3","key":"10.1016\/j.dsp.2026.105902_bib0006","doi-asserted-by":"crossref","first-page":"376","DOI":"10.3390\/e23030376","article-title":"A generative adversarial network for infrared and visible image fusion based on semantic segmentation","volume":"23","author":"Hou","year":"2021","journal-title":"Entropy"},{"key":"10.1016\/j.dsp.2026.105902_bib0007","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/j.inffus.2021.02.008","article-title":"An infrared and visible image fusion method based on multi-scale transformation and norm optimization","volume":"71","author":"Li","year":"2021","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0008","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.infrared.2015.11.002","article-title":"An improved fusion algorithm for infrared and visible images based on multi-scale transform","volume":"74","author":"Li","year":"2016","journal-title":"Infrared. Phys. Technol."},{"key":"10.1016\/j.dsp.2026.105902_bib0009","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIM.2020.2986875","article-title":"Infrared and visible image fusion using visual saliency sparse representation and detail injection model","volume":"70","author":"Yang","year":"2020","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.dsp.2026.105902_bib0010","series-title":"2017 20th International conference on information fusion (Fusion)","first-page":"1","article-title":"Multi-sensor image fusion based on fourth order partial differential equations","author":"Bavirisetti","year":"2017"},{"key":"10.1016\/j.dsp.2026.105902_bib0011","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1016\/j.infrared.2017.04.018","article-title":"Infrared and visible image fusion method based on saliency detection in sparse domain","volume":"83","author":"Liu","year":"2017","journal-title":"Infrared. Phys. Technol."},{"key":"10.1016\/j.dsp.2026.105902_bib0012","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1016\/j.inffus.2015.11.003","article-title":"Perceptual fusion of infrared and visible images through a hybrid multi-scale decomposition with gaussian and bilateral filters","volume":"30","author":"Zhou","year":"2016","journal-title":"Inf. fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0013","article-title":"Infrared and visible image fusion with supervised convolutional neural network","volume":"219","author":"An","year":"2020","journal-title":"Opt. (Stuttg)"},{"key":"10.1016\/j.dsp.2026.105902_bib0014","series-title":"Intelligence Science and Big Data Engineering: 8th International Conference, IScIDE 2018, Lanzhou, China, August 18\u201319, 2018, Revised Selected Papers 8","first-page":"301","article-title":"Infrared-visible image fusion based on convolutional neural networks (CNN)","author":"Ren","year":"2018"},{"key":"10.1016\/j.dsp.2026.105902_bib0015","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.inffus.2020.11.009","article-title":"RXDNFuse: a aggregated residual dense network for infrared and visible image fusion","volume":"69","author":"Long","year":"2021","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0016","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.inffus.2018.09.004","article-title":"FusionGAN: a generative adversarial network for infrared and visible image fusion","volume":"48","author":"Ma","year":"2019","journal-title":"Inf. fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0017","first-page":"1","article-title":"GANMcC: a generative adversarial network with multiclassification constraints for infrared and visible image fusion","volume":"70","author":"Ma","year":"2020","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.dsp.2026.105902_bib0018","series-title":"2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference (ITOEC)","first-page":"457","article-title":"Edge detection algorithm of image fusion based on improved Sobel operator","author":"Zhang","year":"2017"},{"key":"10.1016\/j.dsp.2026.105902_bib0019","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.inffus.2018.02.004","article-title":"Infrared and visible image fusion methods and applications: a survey","volume":"45","author":"Ma","year":"2019","journal-title":"Inf. Fusion"},{"issue":"12","key":"10.1016\/j.dsp.2026.105902_bib0020","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LSENS.2020.3041585","article-title":"PFAF-net: pyramid feature network for multimodal fusion","volume":"4","author":"Raza","year":"2020","journal-title":"IEEE Sens. Lett."},{"issue":"13","key":"10.1016\/j.dsp.2026.105902_bib0021","doi-asserted-by":"crossref","first-page":"14711","DOI":"10.1007\/s10489-022-03463-x","article-title":"multi-scale feature fusion network for image captioning","volume":"52","author":"Prudviraj","year":"2022","journal-title":"Appl. Intell."},{"issue":"3","key":"10.1016\/j.dsp.2026.105902_bib0022","doi-asserted-by":"crossref","first-page":"1181","DOI":"10.1007\/s00371-021-02396-9","article-title":"Image fusion using dual tree discrete wavelet transform and weights optimization","volume":"39","author":"Aghamaleki","year":"2023","journal-title":"Vis. Comput."},{"key":"10.1016\/j.dsp.2026.105902_bib0023","series-title":"ICMLCA 2021; 2nd International Conference on Machine Learning and Computer Application","first-page":"1","article-title":"Infrared and visible image fusion based on non-subsampled contourlet transform","author":"Gao","year":"2021"},{"key":"10.1016\/j.dsp.2026.105902_bib0024","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1109\/ACCESS.2015.2430359","article-title":"A survey of sparse representation: algorithms and applications","volume":"3","author":"Zhang","year":"2015","journal-title":"IEEe Access."},{"key":"10.1016\/j.dsp.2026.105902_bib0025","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":"8","key":"10.1016\/j.dsp.2026.105902_bib0026","doi-asserted-by":"crossref","first-page":"3336","DOI":"10.1109\/TIP.2014.2323127","article-title":"Group-based sparse representation for image restoration","volume":"23","author":"Zhang","year":"2014","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"10.1016\/j.dsp.2026.105902_bib0027","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1109\/JSTSP.2011.2113170","article-title":"Sparse representation for target detection in hyperspectral imagery","volume":"5","author":"Chen","year":"2011","journal-title":"IEEE J. Sel. Top. Signal. Process."},{"key":"10.1016\/j.dsp.2026.105902_bib0028","doi-asserted-by":"crossref","first-page":"477","DOI":"10.1016\/j.infrared.2014.09.019","article-title":"Fusion method for infrared and visible images by using non-negative sparse representation","volume":"67","author":"Wang","year":"2014","journal-title":"Infrared. Phys. Technol."},{"key":"10.1016\/j.dsp.2026.105902_bib0029","doi-asserted-by":"crossref","first-page":"824","DOI":"10.1109\/TCI.2021.3100986","article-title":"Classification saliency-based rule for visible and infrared image fusion","volume":"7","author":"Xu","year":"2021","journal-title":"IEEE Trans. Comput. ImAging"},{"issue":"10","key":"10.1016\/j.dsp.2026.105902_bib0030","doi-asserted-by":"crossref","first-page":"2624","DOI":"10.3390\/rs15102624","article-title":"A novel saliency-based decomposition strategy for infrared and visible image fusion","volume":"15","author":"Qi","year":"2023","journal-title":"Remote Sens. (Basel)"},{"key":"10.1016\/j.dsp.2026.105902_bib0031","doi-asserted-by":"crossref","DOI":"10.1016\/j.sigpro.2020.107936","article-title":"A saliency-based multiscale approach for infrared and visible image fusion","volume":"182","author":"Chen","year":"2021","journal-title":"Signal Process."},{"key":"10.1016\/j.dsp.2026.105902_bib0032","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TIM.2020.3022438","article-title":"SEDRFuse: a symmetric encoder\u2013decoder with residual block network for infrared and visible image fusion","volume":"70","author":"Jian","year":"2020","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.dsp.2026.105902_bib0033","doi-asserted-by":"crossref","first-page":"72","DOI":"10.1016\/j.inffus.2021.02.023","article-title":"RFN-nest: an end-to-end residual fusion network for infrared and visible images","volume":"73","author":"Li","year":"2021","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0034","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.128116","article-title":"A multi-scale information integration framework for infrared and visible image fusion","volume":"600","author":"Yang","year":"2024","journal-title":"Neurocomputing."},{"key":"10.1016\/j.dsp.2026.105902_bib0035","doi-asserted-by":"crossref","DOI":"10.1109\/TIM.2024.3450061","article-title":"PFCFuse: a Poolformer and CNN fusion network for infrared-visible image fusion","author":"Hu","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."},{"issue":"12","key":"10.1016\/j.dsp.2026.105902_bib0036","first-page":"2337","article-title":"Fusion of infrared and visible light images based on improved adaptive dual-channel pulse coupled neural network","volume":"13","author":"Feng","year":"2024","journal-title":"Electron. (Basel)"},{"key":"10.1016\/j.dsp.2026.105902_bib0037","doi-asserted-by":"crossref","DOI":"10.1016\/j.neucom.2024.127353","article-title":"A deep learning and image enhancement based pipeline for infrared and visible image fusion","volume":"578","author":"Qi","year":"2024","journal-title":"Neurocomputing."},{"key":"10.1016\/j.dsp.2026.105902_bib0038","doi-asserted-by":"crossref","first-page":"10145","DOI":"10.1109\/TMM.2024.3405714","article-title":"HitFusion: infrared and visible image fusion for high-level vision tasks using transformer","volume":"26","author":"Chen","year":"2024","journal-title":"IEEE Trans. Multimed."},{"issue":"2","key":"10.1016\/j.dsp.2026.105902_bib0039","doi-asserted-by":"crossref","first-page":"770","DOI":"10.1109\/TCSVT.2023.3289170","article-title":"Cross-modal transformers for infrared and visible image fusion","volume":"34","author":"Park","year":"2023","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.dsp.2026.105902_bib0040","series-title":"Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition","first-page":"27026","article-title":"Text-if: leveraging semantic text guidance for degradation-aware and interactive image fusion","author":"Yi","year":"2024"},{"key":"10.1016\/j.dsp.2026.105902_bib0041","article-title":"PromptFusion: harmonized semantic prompt learning for infrared and visible image fusion","author":"Liu","year":"2024","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"10.1016\/j.dsp.2026.105902_bib0042","doi-asserted-by":"crossref","DOI":"10.1016\/j.patcog.2024.110774","article-title":"CFNet: an infrared and visible image compression fusion network","volume":"156","author":"Xing","year":"2024","journal-title":"Pattern. Recognit."},{"key":"10.1016\/j.dsp.2026.105902_bib0043","series-title":"Advances in Neural Information Processing Systems","first-page":"27","article-title":"Generative adversarial nets","author":"Goodfellow","year":"2014"},{"issue":"30","key":"10.1016\/j.dsp.2026.105902_bib0044","doi-asserted-by":"crossref","first-page":"47751","DOI":"10.1007\/s11042-023-15313-0","article-title":"DGCA: high resolution image inpainting via DR-GAN and contextual attention","volume":"82","author":"Chen","year":"2023","journal-title":"Multimed. Tools. Appl."},{"key":"10.1016\/j.dsp.2026.105902_bib0045","doi-asserted-by":"crossref","first-page":"336","DOI":"10.1016\/j.inffus.2022.12.007","article-title":"AT-GAN: a generative adversarial network with attention and transition for infrared and visible image fusion","volume":"92","author":"Rao","year":"2023","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0046","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/j.inffus.2019.07.005","article-title":"Infrared and visible image fusion via detail preserving adversarial learning","volume":"54","author":"Ma","year":"2020","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0047","doi-asserted-by":"crossref","first-page":"635","DOI":"10.1109\/TMM.2021.3129609","article-title":"Semantic-supervised infrared and visible image fusion via a dual-discriminator generative adversarial network","volume":"25","author":"Zhou","year":"2021","journal-title":"IEEE Trans. Multimed."},{"key":"10.1016\/j.dsp.2026.105902_bib0048","series-title":"Photonics","first-page":"150","article-title":"DDGANSE: dual-discriminator GAN with a squeeze-and-excitation module for infrared and visible image fusion","volume":"9","author":"Wang","year":"2022"},{"issue":"6","key":"10.1016\/j.dsp.2026.105902_bib0049","doi-asserted-by":"crossref","first-page":"4221","DOI":"10.1007\/s00371-023-03078-4","article-title":"Bayesian\u2019s probabilistic strategy for feature fusion from visible and infrared images","volume":"40","author":"Panda","year":"2024","journal-title":"Vis. Comput."},{"issue":"7","key":"10.1016\/j.dsp.2026.105902_bib0050","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."},{"key":"10.1016\/j.dsp.2026.105902_bib0051","series-title":"Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition","first-page":"5906","article-title":"Cddfuse: correlation-driven dual-branch feature decomposition for multi-modality image fusion","author":"Zhao","year":"2023"},{"key":"10.1016\/j.dsp.2026.105902_bib0052","series-title":"Integration of bi-dimensional empirical mode decomposition with two streams deep learning network for infrared and visible image fusion, 2022 30th European Signal Processing Conference (EUSIPCO)","first-page":"493","author":"Panda","year":"2022"},{"key":"10.1016\/j.dsp.2026.105902_bib0053","series-title":"2020 IEEE REGION 10 CONFERENCE (TENCON)","first-page":"251","article-title":"Edge preserving image fusion using intensity variation approach","author":"Panda","year":"2020"},{"key":"10.1016\/j.dsp.2026.105902_bib0054","series-title":"2020 IEEE International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC)","first-page":"1","article-title":"Pixel-level visual and thermal images fusion using maximum and minimum value selection strategy","author":"Panda","year":"2020"},{"key":"10.1016\/j.dsp.2026.105902_bib0055","series-title":"International conference on machine learning","first-page":"214","article-title":"Wasserstein generative adversarial networks","author":"Arjovsky","year":"2017"},{"issue":"1","key":"10.1016\/j.dsp.2026.105902_bib0056","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.dsp.2026.105902_bib0057","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.inffus.2021.12.004","article-title":"Image fusion in the loop of high-level vision tasks: a semantic-aware real-time infrared and visible image fusion network","volume":"82","author":"Tang","year":"2022","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0058","doi-asserted-by":"crossref","first-page":"4980","DOI":"10.1109\/TIP.2020.2977573","article-title":"DDcGAN: a dual-discriminator conditional generative adversarial network for multi-resolution image fusion","volume":"29","author":"Ma","year":"2020","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.dsp.2026.105902_bib0059","doi-asserted-by":"crossref","first-page":"100","DOI":"10.1016\/j.inffus.2016.02.001","article-title":"Infrared and visible image fusion via gradient transfer and total variation minimization","volume":"31","author":"Ma","year":"2016","journal-title":"Inf. Fusion"},{"issue":"5","key":"10.1016\/j.dsp.2026.105902_bib0060","doi-asserted-by":"crossref","first-page":"2614","DOI":"10.1109\/TIP.2018.2887342","article-title":"DenseFuse: a fusion approach to infrared and visible images","volume":"28","author":"Li","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"10.1016\/j.dsp.2026.105902_bib0061","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1016\/j.inffus.2019.07.011","article-title":"IFCNN: a general image fusion framework based on convolutional neural network","volume":"54","author":"Zhang","year":"2020","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0062","series-title":"Proceedings of the Twenty-Ninth International Conference on International Joint Conferences on Artificial Intelligence","first-page":"976","article-title":"Didfuse: deep image decomposition for infrared and visible image fusion","author":"Li","year":"2021"},{"issue":"3","key":"10.1016\/j.dsp.2026.105902_bib0063","doi-asserted-by":"crossref","first-page":"1186","DOI":"10.1109\/TCSVT.2021.3075745","article-title":"Efficient and model-based infrared and visible image fusion via algorithm unrolling","volume":"32","author":"Zhao","year":"2021","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"10.1016\/j.dsp.2026.105902_bib0064","doi-asserted-by":"crossref","DOI":"10.1016\/j.inffus.2023.102147","article-title":"CrossFuse: a novel cross attention mechanism based infrared and visible image fusion approach","volume":"103","author":"Li","year":"2024","journal-title":"Inf. Fusion"},{"key":"10.1016\/j.dsp.2026.105902_bib0065","first-page":"1","article-title":"Lenfusion: a joint low-light enhancement and fusion network for nighttime infrared and visible image fusion","volume":"73","author":"Chen","year":"2024","journal-title":"IEEE Trans. Instrum. Meas."}],"container-title":["Digital Signal Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1051200426000229?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1051200426000229?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T01:06:38Z","timestamp":1773968798000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1051200426000229"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4]]},"references-count":65,"alternative-id":["S1051200426000229"],"URL":"https:\/\/doi.org\/10.1016\/j.dsp.2026.105902","relation":{},"ISSN":["1051-2004"],"issn-type":[{"value":"1051-2004","type":"print"}],"subject":[],"published":{"date-parts":[[2026,4]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"GPF-GAN: An unsupervised generative adversarial network for joint gradient and pixel-constrained fusion of infrared and visible images","name":"articletitle","label":"Article Title"},{"value":"Digital Signal Processing","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.dsp.2026.105902","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"105902"}}