{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,15]],"date-time":"2025-11-15T10:27:53Z","timestamp":1763202473964,"version":"3.37.3"},"reference-count":34,"publisher":"Springer Science and Business Media LLC","issue":"11","license":[{"start":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T00:00:00Z","timestamp":1610323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T00:00:00Z","timestamp":1610323200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Ambient Intell Human Comput"],"published-print":{"date-parts":[[2023,11]]},"DOI":"10.1007\/s12652-020-02584-w","type":"journal-article","created":{"date-parts":[[2021,1,11]],"date-time":"2021-01-11T06:05:40Z","timestamp":1610345140000},"page":"15161-15173","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["An initialization friendly Gaussian mixture model based multi-objective clustering method for SAR images change detection"],"prefix":"10.1007","volume":"14","author":[{"given":"Jiao","family":"Shi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaodong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shenghui","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9892-4460","authenticated-orcid":false,"given":"Yu","family":"Lei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dayong","family":"Tian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,1,11]]},"reference":[{"issue":"3","key":"2584_CR1","doi-asserted-by":"publisher","first-page":"193","DOI":"10.1109\/42.996338","volume":"21","author":"MN Ahmed","year":"2002","unstructured":"Ahmed MN, Yamany SM, Mohamed N, Farag AA, Moriarty T (2002) A modified fuzzy c-means algorithm for bias field estimation and segmentation of mri data. IEEE Trans Med Imaging 21(3):193\u2013199","journal-title":"IEEE Trans Med Imaging"},{"issue":"2","key":"2584_CR2","doi-asserted-by":"publisher","first-page":"141","DOI":"10.14311\/NNW.2016.26.008","volume":"26","author":"U Atasever","year":"2016","unstructured":"Atasever U, Kesikoglu M, Ozkan C (2016) A new artificial intelligence optimization method for pca based unsupervised change detection of remote sensing image data. Neural Netw World 26(2):141\u2013154","journal-title":"Neural Netw World"},{"key":"2584_CR3","doi-asserted-by":"crossref","unstructured":"Bianco V, Memmolo P, Leo M, Montresor S, Distante C, Paturzo M, Picart P, Javidi B, Ferraro P (2018) Strategies for reducing speckle noise in digital holography. Light: Science & Applications 7(1):48","DOI":"10.1038\/s41377-018-0050-9"},{"issue":"8","key":"2584_CR4","doi-asserted-by":"publisher","first-page":"965","DOI":"10.1016\/j.jvcir.2010.09.005","volume":"21","author":"T Celik","year":"2010","unstructured":"Celik T (2010) Image change detection using gaussian mixture model and genetic algorithm. J Visual Commun Image Representation 21(8):965\u2013974","journal-title":"J Visual Commun Image Representation"},{"key":"2584_CR5","doi-asserted-by":"crossref","unstructured":"Chang PC, Chen SH, Zhang Q, Lin JL (2008) Moea\/d for flowshop scheduling problems. In: 2008 IEEE congress on evolutionary computation (IEEE World Congress on Computational Intelligence), IEEE, pp 1433\u20131438","DOI":"10.1109\/CEC.2008.4630982"},{"key":"2584_CR6","doi-asserted-by":"crossref","unstructured":"Chen S, Zhang D (2004) Robust image segmentation using fcm with spatial constraints based on new kernel-induced distance measure. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) 34(4):1907\u20131916","DOI":"10.1109\/TSMCB.2004.831165"},{"issue":"19","key":"2584_CR7","doi-asserted-by":"publisher","first-page":"24699","DOI":"10.1364\/OE.23.024699","volume":"23","author":"G Gong","year":"2015","unstructured":"Gong G, Zhang H, Yao M (2015) Speckle noise reduction algorithm with total variation regularization in optical coherence tomography. Opt Express 23(19):24699\u201324712","journal-title":"Opt Express"},{"issue":"4","key":"2584_CR8","doi-asserted-by":"publisher","first-page":"2141","DOI":"10.1109\/TIP.2011.2170702","volume":"21","author":"M Gong","year":"2012","unstructured":"Gong M, Zhou Z, Ma J (2012) Change detection in synthetic aperture radar images based on image fusion and fuzzy clustering. IEEE Trans Image Process 21(4):2141\u20132151","journal-title":"IEEE Trans Image Process"},{"issue":"1","key":"2584_CR9","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1109\/TFUZZ.2013.2249072","volume":"22","author":"M Gong","year":"2014","unstructured":"Gong M, Su L, Jia M, Chen W (2014) Fuzzy clustering with a modified mrf energy function for change detection in synthetic aperture radar images. IEEE Trans Fuzzy Syst 22(1):98\u2013109","journal-title":"IEEE Trans Fuzzy Syst"},{"issue":"1","key":"2584_CR10","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1109\/TNNLS.2015.2435783","volume":"27","author":"M Gong","year":"2016","unstructured":"Gong M, Zhao J, Liu J, Miao Q, Jiao L (2016) Change detection in synthetic aperture radar images based on deep neural networks. IEEE Trans Neural Netw Learning Syst 27(1):125\u2013138","journal-title":"IEEE Trans Neural Netw Learning Syst"},{"key":"2584_CR11","doi-asserted-by":"publisher","first-page":"876","DOI":"10.1016\/j.swevo.2018.09.008","volume":"44","author":"C Guan","year":"2019","unstructured":"Guan C, Yuen KKF, Coenen F (2019) Particle swarm optimized density-based clustering and classification: supervised and unsupervised learning approaches. Swarm Evol Comput 44:876\u2013896","journal-title":"Swarm Evol Comput"},{"issue":"6","key":"2584_CR12","doi-asserted-by":"publisher","first-page":"856","DOI":"10.1109\/LGRS.2016.2550666","volume":"13","author":"L Jia","year":"2016","unstructured":"Jia L, Li M, Zhang P, Wu Y, Zhu H (2016) Sar image change detection based on multiple kernel k-means clustering with local-neighborhood information. IEEE Geosci Remote Sens Lett 13(6):856\u2013860","journal-title":"IEEE Geosci Remote Sens Lett"},{"issue":"2","key":"2584_CR13","doi-asserted-by":"publisher","first-page":"284","DOI":"10.1109\/TEVC.2008.925798","volume":"13","author":"H Li","year":"2009","unstructured":"Li H, Zhang Q (2009) Multiobjective optimization problems with complicated pareto sets, moea\/d and nsga-ii. IEEE Trans Evol Comput 13(2):284\u2013302","journal-title":"IEEE Trans Evol Comput"},{"key":"2584_CR14","doi-asserted-by":"publisher","first-page":"767","DOI":"10.1016\/j.asoc.2015.10.044","volume":"46","author":"H Li","year":"2016","unstructured":"Li H, Gong M, Wang Q, Liu J, Su L (2016) A multiobjective fuzzy clustering method for change detection in sar images. Appl Soft Comput 46:767\u2013777","journal-title":"Appl Soft Comput"},{"issue":"12","key":"2584_CR15","doi-asserted-by":"publisher","first-page":"2458","DOI":"10.1109\/LGRS.2015.2484220","volume":"12","author":"HC Li","year":"2015","unstructured":"Li HC, Celik T, Longbotham N, Emery WJ (2015) Gabor feature based unsupervised change detection of multitemporal sar images based on two-level clustering. IEEE Geosci Remote Sens Lett 12(12):2458\u20132462","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"2584_CR16","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/j.asoc.2015.05.003","volume":"34","author":"J Liu","year":"2015","unstructured":"Liu J, Gong M, Miao Q, Su L, Li H (2015) Change detection in synthetic aperture radar images based on unsupervised artificial immune systems. Appl Soft Comput 34:151\u2013163","journal-title":"Appl Soft Comput"},{"key":"2584_CR17","first-page":"128","volume":"417","author":"J Ma","year":"2017","unstructured":"Ma J, Jiang J, Liu C, Li Y (2017) Feature guided gaussian mixture model with semi-supervised em and local geometric constraint for retinal image registration. Inform Sci Inform Comput Sci Intell Syst Appl 417:128\u2013142","journal-title":"Inform Sci Inform Comput Sci Intell Syst Appl"},{"key":"2584_CR18","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.swevo.2016.12.005","volume":"33","author":"M Mavrovouniotis","year":"2017","unstructured":"Mavrovouniotis M, Li C, Yang S (2017) A survey of swarm intelligence for dynamic optimization: Algorithms and applications. Swarm Evol Comput 33:1\u201317","journal-title":"Swarm Evol Comput"},{"issue":"1","key":"2584_CR19","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1109\/MGRS.2013.2248301","volume":"1","author":"A Moreira","year":"2013","unstructured":"Moreira A, Prats-Iraola P, Younis M, Krieger G, Hajnsek I, Papathanassiou KP (2013) A tutorial on synthetic aperture radar. IEEE Geosci Remote Sens Mag 1(1):6\u201343","journal-title":"IEEE Geosci Remote Sens Mag"},{"key":"2584_CR20","doi-asserted-by":"publisher","first-page":"546","DOI":"10.1016\/j.swevo.2018.06.010","volume":"44","author":"KR Opara","year":"2019","unstructured":"Opara KR, Arabas J (2019) Differential evolution: a survey of theoretical analyses. Swarm Evol Comput 44:546\u2013558","journal-title":"Swarm Evol Comput"},{"issue":"3","key":"2584_CR21","doi-asserted-by":"publisher","first-page":"264","DOI":"10.3390\/rs8030264","volume":"8","author":"S Pan","year":"2016","unstructured":"Pan S, Shi W, He P, Ming H, Zhang X (2016) Novel approach to unsupervised change detection based on a robust semi-supervised fcm clustering algorithm. Remote Sens 8(3):264","journal-title":"Remote Sens"},{"key":"2584_CR22","doi-asserted-by":"publisher","DOI":"10.1007\/s12652-020-02091-y","author":"B Pandeeswari","year":"2020","unstructured":"Pandeeswari B, Sutha J, Parvathy M (2020) A novel synthetic aperture radar image change detection system using radial basis function-based deep convolutional neural network. J Ambient Intell Human Comput. https:\/\/doi.org\/10.1007\/s12652-020-02091-y","journal-title":"J Ambient Intell Human Comput"},{"key":"2584_CR23","doi-asserted-by":"crossref","unstructured":"Reynolds D (2015) Gaussian mixture models. Encyclopedia of biometrics pp 827\u2013832","DOI":"10.1007\/978-1-4899-7488-4_196"},{"key":"2584_CR24","first-page":"15","volume":"38","author":"S Schlaffer","year":"2015","unstructured":"Schlaffer S, Matgen P, Hollaus M, Wagner W (2015) Flood detection from multi-temporal sar data using harmonic analysis and change detection. Int J Appl Earth Obs Geoinform 38:15\u201324","journal-title":"Int J Appl Earth Obs Geoinform"},{"issue":"1","key":"2584_CR25","doi-asserted-by":"publisher","first-page":"289","DOI":"10.32614\/RJ-2016-021","volume":"8","author":"L Scrucca","year":"2016","unstructured":"Scrucca L, Fop M, Murphy TB, Raftery AE (2016) mclust 5: clustering, classification and density estimation using gaussian finite mixture models. The R Journal 8(1):289\u2013317","journal-title":"The R Journal"},{"key":"2584_CR26","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.rse.2015.01.006","volume":"160","author":"AP Tewkesbury","year":"2015","unstructured":"Tewkesbury AP, Comber AJ, Tate NJ, Lamb A, Fisher PF (2015) A critical synthesis of remotely sensed optical image change detection techniques. Remote Sens Environ 160:1\u201314","journal-title":"Remote Sens Environ"},{"key":"2584_CR27","doi-asserted-by":"crossref","unstructured":"Vellasques E, Sabourin R, Granger E (2012) Gaussian mixture modeling for dynamic particle swarm optimization of recurrent problems. In: Proceedings of the 14th annual conference on Genetic and evolutionary computation, ACM, pp 73\u201380","DOI":"10.1145\/2330163.2330174"},{"issue":"17","key":"2584_CR28","doi-asserted-by":"publisher","first-page":"17719","DOI":"10.1007\/s11042-015-2960-3","volume":"76","author":"G Wei","year":"2017","unstructured":"Wei G, Lv Z, Ming H (2017) Change detection method for remote sensing images based on an improved markov random field. Multimedia Tools Appl 76(17):17719\u201317734","journal-title":"Multimedia Tools Appl"},{"key":"2584_CR29","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1016\/j.swevo.2018.12.009","volume":"45","author":"G Xu","year":"2019","unstructured":"Xu G, Cui Q, Shi X, Ge H, Zhan ZH, Lee HP, Liang Y, Tai R, Wu C (2019) Particle swarm optimization based on dimensional learning strategy. Swarm Evol Comput 45:33\u201351","journal-title":"Swarm Evol Comput"},{"key":"2584_CR30","doi-asserted-by":"publisher","first-page":"88","DOI":"10.1016\/j.neucom.2015.05.140","volume":"195","author":"J Yang","year":"2016","unstructured":"Yang J, Fan J, Ai D, Wang X, Zheng Y, Tang S, Wang Y (2016) Local statistics and non-local mean filter for speckle noise reduction in medical ultrasound image. Neurocomputing 195:88\u201395","journal-title":"Neurocomputing"},{"issue":"6","key":"2584_CR31","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1109\/TEVC.2007.892759","volume":"11","author":"Q Zhang","year":"2007","unstructured":"Zhang Q, Li H (2007) Moea\/d: a multiobjective evolutionary algorithm based on decomposition. IEEE Trans Evol Comput 11(6):712\u2013731","journal-title":"IEEE Trans Evol Comput"},{"key":"2584_CR32","doi-asserted-by":"crossref","unstructured":"Zhang Q, Liu W, Li H (2009) The performance of a new version of moea\/d on cec09 unconstrained mop test instances. In: 2009 IEEE congress on evolutionary computation, IEEE, pp 203\u2013208","DOI":"10.1109\/CEC.2009.4982949"},{"key":"2584_CR33","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1016\/j.patcog.2016.07.040","volume":"61","author":"Y Zheng","year":"2017","unstructured":"Zheng Y, Jiao L, Liu H, Zhang X, Hou B, Wang S (2017) Unsupervised saliency-guided sar image change detection. Pattern Recognit 61:309\u2013326","journal-title":"Pattern Recognit"},{"issue":"1","key":"2584_CR34","doi-asserted-by":"publisher","first-page":"32","DOI":"10.1016\/j.swevo.2011.03.001","volume":"1","author":"A Zhou","year":"2011","unstructured":"Zhou A, Qu BY, Li H, Zhao SZ, Suganthan PN, Zhang Q (2011) Multiobjective evolutionary algorithms: a survey of the state of the art. Swarm Evol Comput 1(1):32\u201349","journal-title":"Swarm Evol Comput"}],"container-title":["Journal of Ambient Intelligence and Humanized Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02584-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12652-020-02584-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12652-020-02584-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,9]],"date-time":"2024-02-09T17:26:55Z","timestamp":1707499615000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12652-020-02584-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,1,11]]},"references-count":34,"journal-issue":{"issue":"11","published-print":{"date-parts":[[2023,11]]}},"alternative-id":["2584"],"URL":"https:\/\/doi.org\/10.1007\/s12652-020-02584-w","relation":{},"ISSN":["1868-5137","1868-5145"],"issn-type":[{"type":"print","value":"1868-5137"},{"type":"electronic","value":"1868-5145"}],"subject":[],"published":{"date-parts":[[2021,1,11]]},"assertion":[{"value":"3 June 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"27 September 2020","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 January 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Compliance with ethical standards"}},{"value":"Authors Xiaodong Liu, Jiao Shi, Yu Lei, Shiying Wang and Lina Huo declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of Interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical Approval"}}]}}