{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T01:41:12Z","timestamp":1763343672207,"version":"3.45.0"},"reference-count":34,"publisher":"Tech Science Press","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.063469","type":"journal-article","created":{"date-parts":[[2025,5,20]],"date-time":"2025-05-20T04:59:39Z","timestamp":1747717179000},"page":"997-1011","source":"Crossref","is-referenced-by-count":0,"title":["A Mask-Guided Latent Low-Rank Representation Method for Infrared and Visible Image Fusion"],"prefix":"10.32604","volume":"84","author":[{"given":"Kezhen","family":"Xie","sequence":"first","affiliation":[]},{"given":"Syed Mohd Zahid Syed Zainal","family":"Ariffin","sequence":"additional","affiliation":[]},{"given":"Muhammad Izzad","family":"Ramli","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/j.inffus.2021.06.008","article-title":"Image fusion meets deep learning: a survey and perspective","volume":"76","author":"Zhang","year":"2021","journal-title":"Inf Fusion"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"108996","DOI":"10.1016\/j.sigpro.2023.108996","article-title":"MCnet: multiscale visible image and infrared image fusion network","volume":"208","author":"Sun","year":"2023","journal-title":"Signal Process"},{"key":"ref3","first-page":"1","article-title":"AFusion: multiscale attention network for infrared and visible image fusion","volume":"71","author":"Li","year":"2022","journal-title":"IEEE Trans Instrum Meas"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"254","DOI":"10.1080\/15472450.2019.1643725","article-title":"Infrared and visible images fusion by using sparse representation and guided filter","volume":"24","author":"Li","year":"2020","journal-title":"J Intell Transp Syst"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1016\/j.infrared.2018.06.029","article-title":"Infrared and visible image fusion method based on sparse features","volume":"92","author":"Ding","year":"2018","journal-title":"Infrared Phys Technol"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"551","DOI":"10.1049\/iet-cvi.2015.0280","article-title":"Image fusion via feature residual and statistical matching","volume":"10","author":"Wang","year":"2016","journal-title":"IET Comput Vis"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"104523","DOI":"10.1016\/j.infrared.2022.104523","article-title":"Joint principal component analysis and total variation for infrared and visible image fusion","volume":"128","author":"Zhang","year":"2023","journal-title":"Infrared Phys Technol"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"e0278055","DOI":"10.1371\/journal.pone.0278055","article-title":"Infrared and visible image fusion algorithm based on spatial domain and image features","volume":"17","author":"Zhao","year":"2022","journal-title":"PLoS One"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"103839","DOI":"10.1016\/j.infrared.2021.103839","article-title":"Infrared and visible image fusion based on variational auto-encoder and infrared feature compensation","volume":"117","author":"Ren","year":"2021","journal-title":"Infrared Phys Technol"},{"key":"ref10","first-page":"1","article-title":"Infrared and visible image fusion based on adversarial feature extraction and stable image reconstruction","volume":"71","author":"Su","year":"2022","journal-title":"IEEE Trans Instrum Meas"},{"key":"ref11","series-title":"Proceedings of the Intelligence Science and Big Data Engineering: 8th International Conference, IScIDE 2018","first-page":"301","article-title":"Infrared-visible image fusion based on convolutional neural networks (CNN)","author":"Ren","year":"2018 Aug 18\u201319"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"3360","DOI":"10.1109\/TCSVT.2021.3109895","article-title":"NFusion: a unified multi-scale densely connected network for infrared and visible image fusion","volume":"32","author":"Wang","year":"2021","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref13","doi-asserted-by":"crossref","first-page":"7458","DOI":"10.1109\/JSEN.2019.2921803","article-title":"Coupled GAN with relativistic discriminators for infrared and visible images fusion","volume":"21","author":"Li","year":"2019","journal-title":"IEEE Sens J"},{"key":"ref14","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":"ref15","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1002\/ima.22242","article-title":"Segmentation method for medical image based on improved GrabCut","volume":"27","author":"Lu","year":"2017","journal-title":"Int J Imaging Syst Technol"},{"key":"ref16","doi-asserted-by":"crossref","unstructured":"Li H, Wu X. Infrared and visible image fusion using latent low-rank representation. arXiv:1804.08992. 2018.","DOI":"10.1109\/ICPR.2018.8546006"},{"key":"ref17","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"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"105344","DOI":"10.1016\/j.imavis.2024.105344","article-title":"Infrared and visible image fusion using quantum computing induced edge preserving filter","volume":"153","author":"Parida","year":"2025","journal-title":"Image Vis Comput"},{"key":"ref19","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":"ref20","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":"ref21","doi-asserted-by":"crossref","first-page":"12797","DOI":"10.1609\/aaai.v34i07.6975","article-title":"Rethinking the image fusion: a fast unified image fusion network based on proportional maintenance of gradient and intensity","volume":"34","author":"Zhang","year":"2020","journal-title":"AAAI"},{"key":"ref22","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":"ref23","doi-asserted-by":"crossref","first-page":"4630","DOI":"10.1109\/TCSVT.2023.3245607","article-title":"Laplacian pyramid fusion network with hierarchical guidance for infrared and visible image fusion","volume":"33","author":"Yao","year":"2023","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"102147","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":"ref25","doi-asserted-by":"crossref","first-page":"2675","DOI":"10.1109\/TCSVT.2024.3493254","article-title":"Infrared-visible image fusion using dual-branch auto-encoder with invertible high-frequency encoding","volume":"35","author":"Liu","year":"2024","journal-title":"IEEE Trans Circuits Syst Video Technol"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"109521","DOI":"10.1016\/j.engappai.2024.109521","article-title":"Color-aware fusion of nighttime infrared and visible images","volume":"139","author":"Yao","year":"2025","journal-title":"Eng Appl Artif Intell"},{"key":"ref27","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.3390\/math11081965","article-title":"Review of GrabCut in image processing","volume":"11","author":"Wang","year":"2023","journal-title":"Mathematics"},{"key":"ref28","unstructured":"Nie F, Pei S, Zheng Z, Wang R, Li X. A greedy strategy for graph cut. arXiv:2412.20035. 2024."},{"key":"ref29","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1007\/978-3-319-12000-3_2","article-title":"Latent low-rank representation","author":"Liu","year":"2014","journal-title":"Low-Rank Sparse Model Vis Anal"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.dib.2017.09.038","article-title":"The TNO multiband image data collection","volume":"15","author":"Toet","year":"2017","journal-title":"Data Brief"},{"key":"ref31","doi-asserted-by":"crossref","first-page":"105344","DOI":"10.1016\/j.infrared.2024.105344","article-title":"SeGFusion: a semantic saliency guided infrared and visible image fusion method","volume":"140","author":"Xiong","year":"2024","journal-title":"Infrared Phys Technol"},{"key":"ref32","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1007\/s40747-022-00792-9","article-title":"Multimodal medical image fusion with convolution sparse representation and mutual information correlation in NSST domain","volume":"9","author":"Guo","year":"2023","journal-title":"Complex Intell Syst"},{"key":"ref33","doi-asserted-by":"crossref","first-page":"3645","DOI":"10.1007\/s11831-020-09518-x","article-title":"Review of various image fusion algorithms and image fusion performance metric","volume":"28","author":"Singh","year":"2021","journal-title":"Arch Comput Methods Eng"},{"key":"ref34","doi-asserted-by":"crossref","first-page":"023522","DOI":"10.1117\/1.2945910","article-title":"Assessment of image fusion procedures using entropy, image quality, and multispectral classification","volume":"2","author":"Roberts","year":"2008","journal-title":"J Appl Remote Sens"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-84-1\/TSP_CMC_63469\/TSP_CMC_63469.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,17]],"date-time":"2025-11-17T01:37:42Z","timestamp":1763343462000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v84n1\/61741"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":34,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.063469","relation":{},"ISSN":["1546-2226"],"issn-type":[{"type":"electronic","value":"1546-2226"}],"subject":[],"published":{"date-parts":[[2025]]}}}