{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T08:35:42Z","timestamp":1775118942552,"version":"3.50.1"},"reference-count":49,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2009,9,30]],"date-time":"2009-09-30T00:00:00Z","timestamp":1254268800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>With the development of satellite and remote sensing techniques, more and more image data from airborne\/satellite sensors have become available. Multi-sensor image fusion seeks to combine information from different images to obtain more inferences than can be derived from a single sensor. In image-based application fields, image fusion has emerged as a promising research area since the end of the last century. The paper presents an overview of recent advances in multi-sensor satellite image fusion. Firstly, the most popular existing fusion algorithms are introduced, with emphasis on their recent improvements. Advances in main applications fields in remote sensing, including object identification, classification, change detection and maneuvering targets tracking, are described. Both advantages and limitations of those applications are then discussed. Recommendations are addressed, including: (1) Improvements of fusion algorithms; (2) Development of \u201calgorithm fusion\u201d methods; (3) Establishment of an automatic quality assessment scheme.<\/jats:p>","DOI":"10.3390\/s91007771","type":"journal-article","created":{"date-parts":[[2009,9,30]],"date-time":"2009-09-30T13:09:17Z","timestamp":1254316157000},"page":"7771-7784","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":278,"title":["Advances in Multi-Sensor Data Fusion: Algorithms and Applications"],"prefix":"10.3390","volume":"9","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4154-5969","authenticated-orcid":false,"given":"Jiang","family":"Dong","sequence":"first","affiliation":[{"name":"Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Dafang","family":"Zhuang","sequence":"additional","affiliation":[{"name":"Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Yaohuan","family":"Huang","sequence":"additional","affiliation":[{"name":"Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]},{"given":"Jingying","family":"Fu","sequence":"additional","affiliation":[{"name":"Data Center for Resources and Environmental Sciences, State Key Lab of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"}]}],"member":"1968","published-online":{"date-parts":[[2009,9,30]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/5.554205","article-title":"An introduction to multisensor data fusion","volume":"85","author":"Hall","year":"1997","journal-title":"Proc. IEEE."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"823","DOI":"10.1080\/014311698215748","article-title":"Multisensor image fusion in remote sensing: concepts, methods and applications","volume":"19","author":"Pohl","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1016\/S1566-2535(01)00056-2","article-title":"Image fusion techniques for remote sensing applications","volume":"3","author":"Simone","year":"2002","journal-title":"Inf. Fusion"},{"key":"ref_4","unstructured":"Vijayaraj, V., Younan, N., and O'Hara, C. (4,, January July). Concepts of image fusion in remote sensing applications. Denver, CO, USA."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Dasarathy, B.V. (2007). A special issue on image fusion: advances in the state of the art. Inf. Fusion, 8.","DOI":"10.1016\/j.inffus.2006.05.003"},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Smith, M.I., and Heather, J.P. Review of image fusion technology in 2005. Orlando, FL, USA.","DOI":"10.1117\/12.597618"},{"key":"ref_7","unstructured":"Blum, R.S., and Liu, Z. (2006). Multi-Sensor Image Fusion and Its Applications; special series on Signal Processing and Communications, CRC Press."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/S0198-9715(98)00051-9","article-title":"Data fusion using artificial neural networks: a case study on multitemporal change analysis","volume":"23","author":"Dai","year":"1999","journal-title":"Comput. Environ. Urban Syst."},{"key":"ref_9","first-page":"657","article-title":"Understanding image fusion","volume":"6","author":"Yun","year":"2004","journal-title":"Photogram. Eng. Remote Sens."},{"key":"ref_10","first-page":"112","article-title":"Comparison between four methods for data fusion of ETM+ multispectral and pan images","volume":"8","author":"Pouran","year":"2005","journal-title":"Geo-spat. Inf. Sci."},{"key":"ref_11","first-page":"33","article-title":"Pyramid methods in image processing","volume":"29","author":"Adelson","year":"1984","journal-title":"RCA Eng."},{"key":"ref_12","first-page":"1605","article-title":"Multi-sensor image fusion based on improved laplacian pyramid transform","volume":"27","author":"Miao","year":"2007","journal-title":"Acta Opti. Sin."},{"key":"ref_13","first-page":"89","article-title":"A pyramid transform of image denoising algorithm based on morphology","volume":"38","author":"Xiang","year":"2009","journal-title":"Acta Photon. Sin."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1109\/34.192463","article-title":"A theory for multiresolution signal decomposition: the wavelet representation","volume":"11","author":"Mallat","year":"1989","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1855","DOI":"10.1016\/j.patcog.2004.03.010","article-title":"Wavelet-based image fusion tutorial","volume":"37","author":"Ganzalo","year":"2004","journal-title":"Pattern Recognit."},{"key":"ref_16","first-page":"81","article-title":"Multisource image fusion based on wavelet transform","volume":"11","author":"Ma","year":"2005","journal-title":"Int. J. Inf. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/j.isprsjprs.2007.05.009","article-title":"Wavelet based image fusion techniques \u2013 An introduction, review and comparison","volume":"62","author":"Krista","year":"2007","journal-title":"ISPRS J. Photogram. Remote Sens."},{"key":"ref_18","unstructured":"Candes, E.J., and Donoho, D.L. (2000). Curvelets-A Surprisingly Effective Nonadaptive Representation for Objects with Edges.Curves and Surfcaces, Vanderbilt University Press."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"136","DOI":"10.1109\/LGRS.2005.845313","article-title":"Fusion of multi-spectral and panchromatic satellite images using the Curvelet transform","volume":"2","author":"Choi","year":"2005","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Donoho, M.N., and Vetterli, M. (2002). Contourlets, Academic Press.","DOI":"10.1016\/S1570-579X(03)80032-0"},{"key":"ref_21","unstructured":"Minh, N., and Martin, V. The contourlet transform: an efficient directional multiresolution image representation. Available online: http:\/\/lcavwww.epfl.ch\/~vetterli\/IP-4-2005.pdf (accessed June 29, 2009)."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/S0034-4257(98)00054-6","article-title":"A neural network model for estimating sea surface chlorophyll and sediments from thematic mapper imagery","volume":"66","author":"Louis","year":"1998","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"1723","DOI":"10.1080\/0143116031000150068","article-title":"An artificial neural network model for estimating crop yields using remotely sensed information","volume":"25","author":"Dong","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"985","DOI":"10.1016\/S0167-8655(02)00029-6","article-title":"Multifocus image fusion using artificial neural networks","volume":"23","author":"Shutao","year":"2002","journal-title":"Pattern Recognit. Lett."},{"key":"ref_25","unstructured":"Thomas, F., and Grzegorz, G. (1995, January April). Optimal fusion of TV and infrared images using artificial neural networks. Orlando, FL, USA."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"1123","DOI":"10.1016\/j.patrec.2007.01.013","article-title":"Multi-focus image fusion using pulse coupled neural network","volume":"28","author":"Huang","year":"2007","journal-title":"Pattern Recognit. Lett."},{"key":"ref_27","first-page":"671","article-title":"Image fusion based on wavelet decomposition and evolutionary strategy","volume":"23","author":"Wu","year":"2003","journal-title":"Acta Opt. Sin."},{"key":"ref_28","first-page":"2040","article-title":"The high-resolution SAR image terrain classification algorithm based on mixed double hint layers RBFN model","volume":"31","author":"Sun","year":"2003","journal-title":"Acta Electron. Sin."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1007\/978-3-540-87656-4_52","article-title":"Image fusion algorithm using RBF neural networks","volume":"9","author":"Zhang","year":"2008","journal-title":"Lect. Notes Comput. Sci."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"287","DOI":"10.1016\/j.neunet.2004.12.003","article-title":"Self-organizing information fusion and hierarchical knowledge discovery- a new framework using ARTMAP neural networks","volume":"18","author":"Gail","year":"2005","journal-title":"Neural Netw."},{"key":"ref_31","unstructured":"Gail, A., Siegfried, M., and Ogas, J. Self-organizing hierarchical knowledge discovery by an ARTMAP image fusion system. Stockholm, Sweden."},{"key":"ref_32","first-page":"821","article-title":"A feature-level image fusion algorithm based on neural networks","volume":"7","author":"Wang","year":"2007","journal-title":"Bioinf. Biomed. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.inffus.2004.06.003","article-title":"An integrated system for automatic road mapping from high-resolution multi-spectral satellite imagery by information fusion","volume":"6","author":"Jin","year":"2005","journal-title":"Inf. Fusion"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"3568","DOI":"10.1016\/j.patcog.2007.05.002","article-title":"Panchromatic sharpening of remote sensing images using a multiscale Kalman filter","volume":"40","author":"Garzelli","year":"2007","journal-title":"Pattern Recognit."},{"key":"ref_35","first-page":"671","article-title":"Image fusion based on wavelet decomposition and evolutionary strategy","volume":"23","author":"Wu","year":"2003","journal-title":"Acta Opt. Sin."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"634","DOI":"10.1109\/TIP.2005.846032","article-title":"Landcover classification in MRF context using Dempster-Shafer fusion for multisensor imagery","volume":"14","author":"Sarkar","year":"2005","journal-title":"IEEE Trans. Image Processing"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Liu, C.P., Ma, X.H., and Cui, Z.M. (2007, January November). Multi-source remote sensing image fusion classification based on DS evidence theory. Wuhan, China. part 2.","DOI":"10.1117\/12.751283"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Rottensteiner, F., Trinder, J., Clode, S., Kubik, K., and Lovell, B. (2004, January August). Building detection by Dempster-Shafer fusion of LIDAR data and multispectral aerial imagery. Cambridge, UK.","DOI":"10.1109\/ICPR.2004.1334203"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1016\/j.eswa.2007.09.067","article-title":"Object-oriented change detection for the city of Harare, Zimbabwe","volume":"36","author":"Ruvimbo","year":"2009","journal-title":"Exp. Syst. Appl."},{"key":"ref_40","first-page":"163","article-title":"A decision level fusion of ADS-40, TABI and AISA data","volume":"2005","author":"Madhavan","year":"2005","journal-title":"Nippon Shashin Sokuryo Gakkai Gakujutsu Koenkai Happyo Ronbunshu"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1696","DOI":"10.1109\/TKDE.2006.183","article-title":"Approaches to multisensor data fusion in target tracking: a survey","volume":"18","author":"Duncan","year":"2006","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"ref_42","first-page":"625","article-title":"Maneuvering vehicle tracking based on multi-sensor fusion","volume":"31","author":"Chen","year":"2005","journal-title":"Acta Autom. Sin."},{"key":"ref_43","first-page":"25","article-title":"An algorithm of tracking a maneuvering target based on ir sensor and radar in dense environment","volume":"7","author":"Liu","year":"2006","journal-title":"J. Air Force Eng. Univ."},{"key":"ref_44","first-page":"43","article-title":"Maneuvering target tracking based on fusion of multi-sensor","volume":"28","author":"Zheng","year":"2006","journal-title":"J. Detect. Control"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Vahdati-khajeh, E. (2004, January January). Tracking the maneuvering targets using multiple scan joint probabilistic data association algorithm. Brighton, UK.","DOI":"10.1049\/ic:20040049"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1016\/j.inffus.2004.06.009","article-title":"An HIS and wavelet integrated approach to improve pan-sharpening visual quality of natural color IKONOS and QuickBird image","volume":"6","author":"Zhang","year":"2005","journal-title":"Inf. Fusion."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1016\/j.inffus.2007.03.002","article-title":"Theoretical analysis of an information-based quality measure for image fusion","volume":"9","author":"Chen","year":"2008","journal-title":"Inf. Fusion"},{"key":"ref_48","unstructured":"Zhao, J.Y., Laganiere, R., and Liu, Z. (1,, January August). Image fusion algorithm assessment based on feature measurement. Beijing, China."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.inffus.2006.04.001","article-title":"Image fusion: advances in the state of the art","volume":"8","author":"Goshtasby","year":"2007","journal-title":"Inf. Fusion."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/9\/10\/7771\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T22:11:16Z","timestamp":1760220676000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/9\/10\/7771"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2009,9,30]]},"references-count":49,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2009,10]]}},"alternative-id":["s91007771"],"URL":"https:\/\/doi.org\/10.3390\/s91007771","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2009,9,30]]}}}