{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T19:17:30Z","timestamp":1773429450579,"version":"3.50.1"},"reference-count":69,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T00:00:00Z","timestamp":1641686400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T00:00:00Z","timestamp":1641686400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["41801308"],"award-info":[{"award-number":["41801308"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Earth Sci Inform"],"published-print":{"date-parts":[[2022,3]]},"DOI":"10.1007\/s12145-021-00734-y","type":"journal-article","created":{"date-parts":[[2022,1,9]],"date-time":"2022-01-09T00:02:42Z","timestamp":1641686562000},"page":"369-381","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A comparative study of threshold selection methods for change detection from very high-resolution remote sensing images"],"prefix":"10.1007","volume":"15","author":[{"given":"Huaqiao","family":"Xing","sequence":"first","affiliation":[]},{"given":"Linye","family":"Zhu","sequence":"additional","affiliation":[]},{"given":"Bingyao","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Chang","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Jingge","family":"Niu","sequence":"additional","affiliation":[]},{"given":"Xuehan","family":"Li","sequence":"additional","affiliation":[]},{"given":"Yongyu","family":"Feng","sequence":"additional","affiliation":[]},{"given":"Wenbo","family":"Fang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,9]]},"reference":[{"key":"734_CR1","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1016\/0734-189X(89)90051-0","volume":"47","author":"AS Abutaleb","year":"1989","unstructured":"Abutaleb AS (1989) Automatic thresholding of gray-level pictures using two-dimensional entropy. Comput Vision, Graph Image Process 47:22\u201332. https:\/\/doi.org\/10.1016\/0734-189X(89)90051-0","journal-title":"Comput Vision, Graph Image Process"},{"key":"734_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2015.02.029","volume":"83","author":"S Aja-Fern\u00e1ndez","year":"2015","unstructured":"Aja-Fern\u00e1ndez S, Curiale AH, Vegas-S\u00e1nchez-Ferrero G (2015) A local fuzzy thresholding methodology for multiregion image segmentation. Knowl Based Syst 83:1\u201312. https:\/\/doi.org\/10.1016\/j.knosys.2015.02.029","journal-title":"Knowl Based Syst"},{"key":"734_CR3","doi-asserted-by":"publisher","first-page":"62","DOI":"10.5815\/ijigsp.2013.12.09","volume":"5","author":"M Akther","year":"2013","unstructured":"Akther M, Ahmed MK, Hasan MZ (2013) Detection of vehicle\u2019s number plate at nighttime using Iterative Threshold Segmentation (ITS) algorithm. Int J Image Graph Signal Process 5:62\u201370. https:\/\/doi.org\/10.5815\/ijigsp.2013.12.09","journal-title":"Int J Image Graph Signal Process"},{"key":"734_CR4","doi-asserted-by":"publisher","first-page":"2779","DOI":"10.3390\/rs11232779","volume":"11","author":"K Awty-Carroll","year":"2019","unstructured":"Awty-Carroll K, Bunting P, Hardy A, Bell G (2019) An evaluation and comparison of four dense time series change detection methods using simulated data. Remote Sens 11:2779\u20132808. https:\/\/doi.org\/10.3390\/rs11232779","journal-title":"Remote Sens"},{"key":"734_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s42979-020-00136-9","volume":"1","author":"D Baby","year":"2020","unstructured":"Baby D, Devaraj SJ, Mathew S et al (2020) A performance comparison of supervised and unsupervised image segmentation methods. SN Comput Sci 1:1\u20136. https:\/\/doi.org\/10.1007\/s42979-020-00136-9","journal-title":"SN Comput Sci"},{"key":"734_CR6","doi-asserted-by":"publisher","first-page":"2196","DOI":"10.1109\/TGRS.2011.2171493","volume":"50","author":"F Bovolo","year":"2012","unstructured":"Bovolo F, Marchesi S, Bruzzone L (2012) A framework for automatic and unsupervised detection of multiple changes in multitemporal images. IEEE Trans Geosci Remote Sens 50:2196\u20132212","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"734_CR7","doi-asserted-by":"publisher","first-page":"1171","DOI":"10.1109\/36.843009","volume":"38","author":"L Bruzzone","year":"2000","unstructured":"Bruzzone L, Member S (2000) Automatic analysis of the difference image for unsupervised change detection. IEEE Trans Geosci Remote Sens 38:1171\u20131182. https:\/\/doi.org\/10.1109\/36.843009","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"734_CR8","doi-asserted-by":"publisher","first-page":"858","DOI":"10.1109\/36.602528","volume":"35","author":"L Bruzzone","year":"1997","unstructured":"Bruzzone L, Serpico SB (1997) An iterative technique for the detection of land-cover transitions in multitemporal remote-sensing images. IEEE Trans Geosci Remote Sens 35:858\u2013867. https:\/\/doi.org\/10.1109\/36.602528","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"734_CR9","doi-asserted-by":"publisher","first-page":"868","DOI":"10.1049\/el:20020594","volume":"38","author":"L Cao","year":"2002","unstructured":"Cao L, Shi ZK, Cheng EKW (2002) Fast automatic multilevel thresholding method. Electron Lett 38:868\u2013870. https:\/\/doi.org\/10.1049\/el:20020594","journal-title":"Electron Lett"},{"key":"734_CR10","doi-asserted-by":"publisher","first-page":"571","DOI":"10.1016\/j.compmedimag.2005.04.003","volume":"29","author":"KS Chuang","year":"2005","unstructured":"Chuang KS, Jan ML, Wu J et al (2005) A maximum likelihood expectation maximization algorithm with thresholding. Comput Med Imaging Graph 29:571\u2013578. https:\/\/doi.org\/10.1016\/j.compmedimag.2005.04.003","journal-title":"Comput Med Imaging Graph"},{"key":"734_CR11","first-page":"710","volume":"14","author":"GAO Cong-shan","year":"2010","unstructured":"Cong-shan GAO, Hong Z, Chao W (2010) SAR change detection based on Generalized Gamma distribution divergence and auto-threshold segmentation. J Remote Sens 14:710\u2013724","journal-title":"J Remote Sens"},{"key":"734_CR12","doi-asserted-by":"publisher","first-page":"1010","DOI":"10.1016\/j.patrec.2009.12.025","volume":"31","author":"N Coudray","year":"2010","unstructured":"Coudray N, Buessler JL, Urban JP (2010) Robust threshold estimation for images with unimodal histograms. Pattern Recognit Lett 31:1010\u20131019. https:\/\/doi.org\/10.1016\/j.patrec.2009.12.025","journal-title":"Pattern Recognit Lett"},{"key":"734_CR13","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1007\/s10479-005-5724-z","volume":"134","author":"PT De Boer","year":"2005","unstructured":"De Boer PT, Kroese DP, Mannor S, Rubinstein RY (2005) A tutorial on the cross-entropy method. Ann Oper Res 134:19\u201367. https:\/\/doi.org\/10.1007\/s10479-005-5724-z","journal-title":"Ann Oper Res"},{"key":"734_CR14","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.isprsjprs.2020.01.026","volume":"161","author":"P Du","year":"2020","unstructured":"Du P, Wang X, Chen D et al (2020) An improved change detection approach using tri-temporal logic-verified change vector analysis. ISPRS J Photogramm Remote Sens 161:278\u2013293. https:\/\/doi.org\/10.1016\/j.isprsjprs.2020.01.026","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"734_CR15","first-page":"68","volume":"7","author":"C Eyupoglu","year":"2017","unstructured":"Eyupoglu C (2017) Implementation of Bernsen\u2019s Locally Adaptive Binarization Method for Gray Scale Images. J Sci Technol 7:68\u201372","journal-title":"J Sci Technol"},{"key":"734_CR16","doi-asserted-by":"publisher","first-page":"662","DOI":"10.1016\/j.patrec.2006.11.005","volume":"28","author":"SKS Fan","year":"2007","unstructured":"Fan SKS, Lin Y (2007) A multi-level thresholding approach using a hybrid optimal estimation algorithm. Pattern Recognit Lett 28:662\u2013669. https:\/\/doi.org\/10.1016\/j.patrec.2006.11.005","journal-title":"Pattern Recognit Lett"},{"key":"734_CR17","doi-asserted-by":"publisher","first-page":"1676","DOI":"10.1109\/TBME.2010.2041232","volume":"57","author":"H Fatakdawala","year":"2010","unstructured":"Fatakdawala H, Xu J, Basavanhally A et al (2010) Expectation-maximization-driven geodesic active contour with overlap resolution (EMaGACOR): Application to lymphocyte segmentation on breast cancer histopathology. IEEE Trans Biomed Eng 57:1676\u20131689. https:\/\/doi.org\/10.1109\/TBME.2010.2041232","journal-title":"IEEE Trans Biomed Eng"},{"key":"734_CR18","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1109\/TGRS.1990.572980","volume":"28","author":"T Fung","year":"1990","unstructured":"Fung T (1990) An assessment of TM imagery for land-cover change detection. IEEE Trans Geosci Remote Sens 28:681\u2013684. https:\/\/doi.org\/10.1109\/TGRS.1990.572980","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"734_CR19","doi-asserted-by":"publisher","first-page":"4001","DOI":"10.3390\/rs12234001","volume":"12","author":"E Ghaderpour","year":"2020","unstructured":"Ghaderpour E, Vujadinovic T (2020) Change detection within remotely sensed satellite image time series via spectral Analysis. Remote Sens 12:4001. https:\/\/doi.org\/10.3390\/rs12234001","journal-title":"Remote Sens"},{"key":"734_CR20","doi-asserted-by":"publisher","first-page":"4551","DOI":"10.1109\/JSTARS.2018.2882412","volume":"11","author":"M Ghanbari","year":"2018","unstructured":"Ghanbari M, Akbari V (2018) Unsupervised change detection in polarimetric SAR data with the Hotelling-Lawley trace statistic and minimum-error thresholding. IEEE J Sel Top Appl Earth Obs Remote Sens 11:4551\u20134562. https:\/\/doi.org\/10.1109\/JSTARS.2018.2882412","journal-title":"IEEE J Sel Top Appl Earth Obs Remote Sens"},{"key":"734_CR21","doi-asserted-by":"publisher","first-page":"96","DOI":"10.1080\/22797254.2018.1561156","volume":"52","author":"M Hao","year":"2019","unstructured":"Hao M, Tan M, Zhang H (2019) A change detection framework by fusing threshold and clustering methods for optical medium resolution remote sensing images. Eur J Remote Sens 52:96\u2013106. https:\/\/doi.org\/10.1080\/22797254.2018.1561156","journal-title":"Eur J Remote Sens"},{"key":"734_CR22","doi-asserted-by":"publisher","unstructured":"Hasanlau M, Seydi ST (2018) Sensitivity analysis on performance of different unsupervised threshold selection methods in hyperspectral change detection. 2018 10th IAPR Work Pattern Recognit Remote Sensing, PRRS 2018. https:\/\/doi.org\/10.1109\/PRRS.2018.8486355","DOI":"10.1109\/PRRS.2018.8486355"},{"key":"734_CR23","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1016\/j.isprsjprs.2018.10.008","volume":"146","author":"Y Hu","year":"2018","unstructured":"Hu Y, Dong Y, Batunacun (2018) An automatic approach for land-change detection and land updates based on integrated NDVI timing analysis and the CVAPS method with GEE support. ISPRS J Photogramm Remote Sens 146:347\u2013359. https:\/\/doi.org\/10.1016\/j.isprsjprs.2018.10.008","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"734_CR24","doi-asserted-by":"publisher","first-page":"1469","DOI":"10.1109\/TPAMI.2013.200","volume":"36","author":"P Isola","year":"2014","unstructured":"Isola P, Xiao J, Parikh D et al (2014) What makes a photograph memorable? IEEE Trans Pattern Anal Mach Intell 36:1469\u20131482. https:\/\/doi.org\/10.1109\/TPAMI.2013.200","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"734_CR25","doi-asserted-by":"publisher","first-page":"1339","DOI":"10.1016\/S0031-3203(99)00122-3","volume":"33","author":"CV Jawahar","year":"2000","unstructured":"Jawahar CV, Biswas PK, Ray AK (2000) Analysis of fuzzy thresholding schemes. Pattern Recognit 33:1339\u20131349. https:\/\/doi.org\/10.1016\/S0031-3203(99)00122-3","journal-title":"Pattern Recognit"},{"key":"734_CR26","doi-asserted-by":"publisher","first-page":"2658","DOI":"10.2307\/j.ctt1ffjjf6.16","volume":"55","author":"B Jones","year":"2017","unstructured":"Jones B (2017) Superpixel-based difference representation learning for change detection in multispectral remote sensing images. IEEE Trans Geosci Remote Sens 55:2658\u20132673. https:\/\/doi.org\/10.2307\/j.ctt1ffjjf6.16","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"734_CR27","doi-asserted-by":"publisher","first-page":"273","DOI":"10.1016\/0734-189X(85)90125-2","volume":"29","author":"JN Kapur","year":"1985","unstructured":"Kapur JN, Sahoo PK, Wong AKC (1985) A new method for grey-level picture thresholding using the entropy of the histogram. Comput Vision Graph Image Process 29:273\u2013285","journal-title":"Comput Vision Graph Image Process"},{"key":"734_CR28","doi-asserted-by":"publisher","first-page":"125","DOI":"10.1016\/0734-189X(85)90093-3","volume":"30","author":"J Kittler","year":"1985","unstructured":"Kittler J, Illingworth J, F\u00f6glein J (1985) Threshold selection based on a simple image statistic. Comput Vision Graph Image Process 30:125\u2013147. https:\/\/doi.org\/10.1016\/0734-189X(85)90093-3","journal-title":"Comput Vision Graph Image Process"},{"key":"734_CR29","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1016\/0734-189X(90)90053-X","volume":"52","author":"SU Lee","year":"1990","unstructured":"Lee SU, Yoon Chung S, Park RH (1990) A comparative performance study of several global thresholding techniques for segmentation. Comput Vision Graph Image Process 52:171\u2013190. https:\/\/doi.org\/10.1016\/0734-189X(90)90053-X","journal-title":"Comput Vision Graph Image Process"},{"key":"734_CR30","doi-asserted-by":"publisher","first-page":"617","DOI":"10.1016\/0031-3203(93)90115-D","volume":"26","author":"CH Li","year":"1993","unstructured":"Li CH, Leet CK (1993) Minimum cross entropy thresholding. Pattern Recognit 26:617\u2013625","journal-title":"Pattern Recognit"},{"key":"734_CR31","doi-asserted-by":"publisher","first-page":"771","DOI":"10.1016\/S0167-8655(98)00057-9","volume":"19","author":"CH Li","year":"1998","unstructured":"Li CH, Tam PKS (1998) An iterative algorithm for minimum cross entropy thresholding. Pattern Recognit Lett 19:771\u2013776. https:\/\/doi.org\/10.1016\/S0167-8655(98)00057-9","journal-title":"Pattern Recognit Lett"},{"key":"734_CR32","doi-asserted-by":"publisher","first-page":"104","DOI":"10.2197\/ipsjtcva.7.104","volume":"7","author":"CF Liew","year":"2015","unstructured":"Liew CF, Yairi T (2015) Facial expression recognition and analysis: A comparison study of feature descriptors. IPSJ Trans Comput Vis Appl 7:104\u2013120. https:\/\/doi.org\/10.2197\/ipsjtcva.7.104","journal-title":"IPSJ Trans Comput Vis Appl"},{"key":"734_CR33","doi-asserted-by":"publisher","first-page":"410","DOI":"10.3390\/ijgi7100410","volume":"7","author":"H Liu","year":"2018","unstructured":"Liu H, Yang M, Chen J et al (2018) Line-constrained shape feature for building change detection in VHR remote sensing imagery. ISPRS Int J Geo-Inf 7:410\u2013429. https:\/\/doi.org\/10.3390\/ijgi7100410","journal-title":"ISPRS Int J Geo-Inf"},{"key":"734_CR34","doi-asserted-by":"publisher","first-page":"1112","DOI":"10.3390\/rs9111112","volume":"9","author":"ZY Lv","year":"2017","unstructured":"Lv ZY, Shi WZ, Zhou XC, Benediktsson JA (2017) Semi-automatic system for land cover change detection using Bi-temporal remote sensing images. Remote Sens 9:1112\u20131132. https:\/\/doi.org\/10.3390\/rs9111112","journal-title":"Remote Sens"},{"key":"734_CR35","doi-asserted-by":"publisher","first-page":"9554","DOI":"10.1109\/TGRS.2019.2927659","volume":"57","author":"ZY Lv","year":"2019","unstructured":"Lv ZY, Liu TF, Zhang P et al (2019) Novel adaptive histogram trend similarity approach for land cover change detection by using bitemporal very-high-resolution remote sensing images. IEEE Trans Geosci Remote Sens 57:9554\u20139574. https:\/\/doi.org\/10.1109\/TGRS.2019.2927659","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"734_CR36","doi-asserted-by":"publisher","unstructured":"Mahdianpari M, Salehi B, Mohammadimanesh F et al (2020) Big data for a big country: the first generation of Canadian Wetland Inventory Map at a spatial resolution of 10-m Using Sentinel-1 and Sentinel-2 data on the Google earth engine cloud computing platform. Can J Remote Sens 46:15\u201333. https:\/\/doi.org\/10.1080\/07038992.2019.1711366","DOI":"10.1080\/07038992.2019.1711366"},{"key":"734_CR37","unstructured":"Malila WA (1980) Change vector analysis: an approach for detecting forest changes with landsat. Proc Soc Photo-Optical Instrum Eng 326\u2013336"},{"key":"734_CR38","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.knosys.2013.04.011","volume":"48","author":"J Mao","year":"2013","unstructured":"Mao J, Yao D, Wang C (2013) A novel cross-entropy and entropy measures of IFSs and their applications. Knowl-Based Syst 48:37\u201345. https:\/\/doi.org\/10.1016\/j.knosys.2013.04.011","journal-title":"Knowl-Based Syst"},{"key":"734_CR39","doi-asserted-by":"publisher","first-page":"3528","DOI":"10.3390\/s120303528","volume":"12","author":"I Molina","year":"2012","unstructured":"Molina I, Martinez E, Arquero A et al (2012) Evaluation of a change detection methodology by means of binary thresholding algorithms and informational fusion processes. Sensors 12:3528\u20133561. https:\/\/doi.org\/10.3390\/s120303528","journal-title":"Sensors"},{"key":"734_CR40","doi-asserted-by":"publisher","first-page":"1277","DOI":"10.1016\/0031-3203(93)90135-J","volume":"26","author":"RP Nikhil","year":"1993","unstructured":"Nikhil RP, Sankar KP (1993) A Review on Image Segmentation Techniques. Pattern Recognit 26:1277\u20131294","journal-title":"Pattern Recognit"},{"key":"734_CR41","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/tsmc.1979.4310076","volume":"\u20139","author":"N Otsu","year":"1979","unstructured":"Otsu N (1979) Threshold selection method from gray-level histograms. IEEE Trans Syst Man Cybern SMC \u20139:62\u201366. https:\/\/doi.org\/10.1109\/tsmc.1979.4310076","journal-title":"IEEE Trans Syst Man Cybern SMC"},{"key":"734_CR42","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1016\/0167-8655(83)90053-3","volume":"1","author":"SK Pal","year":"1983","unstructured":"Pal SK, King RA, Hashim AA (1983) Automatic grey level thresholding through index of fuzziness and entropy. Pattern Recognit Lett 1:141\u2013146. https:\/\/doi.org\/10.1016\/0167-8655(83)90053-3","journal-title":"Pattern Recognit Lett"},{"key":"734_CR43","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1016\/0165-1684(93)90107-L","volume":"33","author":"NR Pal","year":"1993","unstructured":"Pal NR, Bhandari D (1993) Image thresholding: Some new techniques. Sig Process 33:139\u2013158. https:\/\/doi.org\/10.1016\/0165-1684(93)90107-L","journal-title":"Sig Process"},{"key":"734_CR44","doi-asserted-by":"publisher","first-page":"6071","DOI":"10.1080\/01431161.2010.507793","volume":"32","author":"S Patra","year":"2011","unstructured":"Patra S, Ghosh S, Ghosh A (2011) Histogram thresholding for unsupervised change detection of remote sensing images. Int J Remote Sens 32:6071\u20136089. https:\/\/doi.org\/10.1080\/01431161.2010.507793","journal-title":"Int J Remote Sens"},{"key":"734_CR45","doi-asserted-by":"publisher","first-page":"742","DOI":"10.3390\/rs13040742","volume":"13","author":"J Peng","year":"2021","unstructured":"Peng J, Mei X, Li W et al (2021) Scene complexity: a new perspective on understanding the scene semantics of remote sensing and designing image-adaptive convolutional neural networks. Remote Sens 13:742. https:\/\/doi.org\/10.3390\/rs13040742","journal-title":"Remote Sens"},{"key":"734_CR46","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1109\/TPAMI.1987.4767981","volume":"9","author":"A Perez","year":"1987","unstructured":"Perez A, Gonzalez RC (1987) An iterative thresholding algorthm for image segmentation. IEEE Trans Pattern Anal Mach Intell 9:742\u2013751. https:\/\/doi.org\/10.1109\/TPAMI.1987.4767981","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"734_CR47","doi-asserted-by":"publisher","first-page":"630","DOI":"10.1109\/tsmc.1978.4310039","volume":"8","author":"TW Ridler","year":"1978","unstructured":"Ridler TW, Calvard S (1978) Picture thresholding using an iterative slection method. IEEE Trans Syst Man Cybern SMC 8:630\u2013632. https:\/\/doi.org\/10.1109\/tsmc.1978.4310039","journal-title":"IEEE Trans Syst Man Cybern SMC"},{"key":"734_CR48","doi-asserted-by":"publisher","first-page":"2083","DOI":"10.1016\/S0031-3203(00)00136-9","volume":"34","author":"PL Rosin","year":"2001","unstructured":"Rosin PL (2001) Unimodal thresholding. Pattern Recognit 34:2083\u20132096. https:\/\/doi.org\/10.1016\/S0031-3203(00)00136-9","journal-title":"Pattern Recognit"},{"key":"734_CR49","unstructured":"Saha S (2009) An analytical study of different document image Binarization methods. IEEE Natl Conf Comput Commun Syst, 71\u201374"},{"key":"734_CR50","doi-asserted-by":"publisher","first-page":"3677","DOI":"10.1109\/TGRS.2018.2886643","volume":"57","author":"S Saha","year":"2019","unstructured":"Saha S, Bovolo F, Bruzzone L (2019) Unsupervised deep change vector analysis for multiple-change detection in VHR Images. IEEE Trans Geosci Remote Sens 57:3677\u20133693. https:\/\/doi.org\/10.1109\/TGRS.2018.2886643","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"734_CR51","first-page":"1","volume":"99","author":"S Saha","year":"2020","unstructured":"Saha S, Member S, Solano-correa YT et al (2020) Unsupervised deep transfer learning-based change detection for HR multispectral images. IEEE Geosci Remote Sens Lett 99:1\u20135","journal-title":"IEEE Geosci Remote Sens Lett"},{"key":"734_CR52","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1016\/0734-189X(88)90022-9","volume":"41","author":"PK Sahoo","year":"1988","unstructured":"Sahoo PK, Soltani S, Wong AKC (1988) A survey of thresholding techniques. Comput Vision Graph Image Process 41:233\u2013260. https:\/\/doi.org\/10.1016\/0734-189X(88)90022-9","journal-title":"Comput Vision Graph Image Process"},{"key":"734_CR53","doi-asserted-by":"publisher","first-page":"1246","DOI":"10.1016\/j.cageo.2010.02.007","volume":"36","author":"S Schl\u00fcter","year":"2010","unstructured":"Schl\u00fcter S, Weller U, Vogel HJ (2010) Segmentation of X-ray microtomography images of soil using gradient masks. Comput Geosci 36:1246\u20131251. https:\/\/doi.org\/10.1016\/j.cageo.2010.02.007","journal-title":"Comput Geosci"},{"key":"734_CR54","doi-asserted-by":"publisher","first-page":"151","DOI":"10.1016\/S0167-8655(99)00142-7","volume":"21","author":"M Sezgin","year":"2000","unstructured":"Sezgin M, Ta\u015falt\u00edn R (2000) A new dichotomization technique to multilevel thresholding devoted to inspection applications. Pattern Recognit Lett 21:151\u2013161. https:\/\/doi.org\/10.1016\/S0167-8655(99)00142-7","journal-title":"Pattern Recognit Lett"},{"key":"734_CR55","doi-asserted-by":"publisher","first-page":"989","DOI":"10.1080\/01431168908903939","volume":"10","author":"A Singh","year":"1989","unstructured":"Singh A (1989) Review Articlel: Digital change detection techniques using remotely-sensed data. Int J Remote Sens 10:989\u20131003. https:\/\/doi.org\/10.1080\/01431168908903939","journal-title":"Int J Remote Sens"},{"key":"734_CR56","doi-asserted-by":"publisher","first-page":"2283","DOI":"10.1007\/s10994-020-05926-z","volume":"109","author":"D Wang","year":"2020","unstructured":"Wang D, Guo X, Li S, Xu J (2020) Robust high dimensional expectation maximization algorithm via trimmed hard thresholding. Mach Learn 109:2283\u20132311. https:\/\/doi.org\/10.1007\/s10994-020-05926-z","journal-title":"Mach Learn"},{"key":"734_CR57","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1016\/j.sigpro.2015.09.020","volume":"124","author":"C Wu","year":"2016","unstructured":"Wu C, Zhang L, Zhang L (2016) A scene change detection framework for multi-temporal very high resolution remote sensing images. Sig Process 124:184\u2013197. https:\/\/doi.org\/10.1016\/j.sigpro.2015.09.020","journal-title":"Sig Process"},{"key":"734_CR58","doi-asserted-by":"publisher","first-page":"2367","DOI":"10.1007\/springerreference_65703","volume":"55","author":"C Wu","year":"2017","unstructured":"Wu C, Zhang L, Du B (2017) Kernel slow feature analysis for scene change detection. IEEE Trans Geosci Remote Sens 55:2367\u20132384. https:\/\/doi.org\/10.1007\/springerreference_65703","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"734_CR59","doi-asserted-by":"publisher","first-page":"1133","DOI":"10.1016\/j.rse.2009.02.004","volume":"113","author":"G Xian","year":"2009","unstructured":"Xian G, Homer C, Fry J (2009) Updating the 2001 National Land Cover Database land cover classification to 2006 by using Landsat imagery change detection methods. Remote Sens Environ 113:1133\u20131147. https:\/\/doi.org\/10.1016\/j.rse.2009.02.004","journal-title":"Remote Sens Environ"},{"key":"734_CR60","doi-asserted-by":"publisher","first-page":"402","DOI":"10.1016\/j.isprsjprs.2016.07.003","volume":"119","author":"P Xiao","year":"2016","unstructured":"Xiao P, Zhang X, Wang D et al (2016) Change detection of built-up land: A framework of combining pixel-based detection and object-based recognition. ISPRS J Photogramm Remote Sens 119:402\u2013414. https:\/\/doi.org\/10.1016\/j.isprsjprs.2016.07.003","journal-title":"ISPRS J Photogramm Remote Sens"},{"key":"734_CR61","doi-asserted-by":"publisher","first-page":"4284","DOI":"10.1080\/01431161.2021.1892860","volume":"42","author":"H Xing","year":"2021","unstructured":"Xing H, Zhu L, Hou D, Zhang T (2021) Integrating change magnitude maps of spectrally enhanced multi-features for land cover change detection. Int J Remote Sens 42:4284\u20134308. https:\/\/doi.org\/10.1080\/01431161.2021.1892860","journal-title":"Int J Remote Sens"},{"key":"734_CR62","doi-asserted-by":"publisher","first-page":"793","DOI":"10.1016\/j.patrec.2012.01.002","volume":"33","author":"JH Xue","year":"2012","unstructured":"Xue JH, Zhang YJ (2012) Ridler and Calvard\u2019s, Kittler and Illingworth\u2019s and Otsu\u2019s methods for image thresholding. Pattern Recognit Lett 33:793\u2013797. https:\/\/doi.org\/10.1016\/j.patrec.2012.01.002","journal-title":"Pattern Recognit Lett"},{"key":"734_CR63","doi-asserted-by":"publisher","first-page":"665","DOI":"10.1007\/978-3-540-92841-6_163","volume":"23","author":"P Yampri","year":"2009","unstructured":"Yampri P, Sotthivirat S, Gansawat D et al (2009) Performance comparison of bone segmentation on dental CT images. IFMBE Proc 23:665\u2013668. https:\/\/doi.org\/10.1007\/978-3-540-92841-6_163","journal-title":"IFMBE Proc"},{"key":"734_CR64","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/j.rse.2006.05.020","volume":"107","author":"Y Yang","year":"2007","unstructured":"Yang Y, Di Girolamo L, Mazzoni D (2007) Selection of the automated thresholding algorithm for the Multi-angle Imaging SpectroRadiometer Radiometric Camera-by-Camera Cloud Mask over land. Remote Sens Environ 107:159\u2013171. https:\/\/doi.org\/10.1016\/j.rse.2006.05.020","journal-title":"Remote Sens Environ"},{"key":"734_CR65","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1109\/JSTARS.2019.2896233","volume":"12","author":"G Yang","year":"2019","unstructured":"Yang G, Li HC, Yang W et al (2019) Variational Bayesian change detection of remote sensing images based on spatially variant gaussian mixture model and separability criterion. IEEE J Sel Top Appl Earth Obs Remote Sens 12:849\u2013861. https:\/\/doi.org\/10.1109\/JSTARS.2019.2896233","journal-title":"IEEE J Sel Top Appl Earth Obs Remote Sens"},{"key":"734_CR66","doi-asserted-by":"publisher","first-page":"370","DOI":"10.1109\/83.366472","volume":"4","author":"JC Yen","year":"1995","unstructured":"Yen JC, Chang FJ, Chang S (1995) A new criterion for automatic multilevel thresholding. IEEE Trans Image Process 4:370\u2013378. https:\/\/doi.org\/10.1109\/83.366472","journal-title":"IEEE Trans Image Process"},{"key":"734_CR67","doi-asserted-by":"publisher","first-page":"386","DOI":"10.1016\/j.rse.2018.11.038","volume":"221","author":"G Zhang","year":"2019","unstructured":"Zhang G, Yao T, Chen W et al (2019) Regional differences of lake evolution across China during 1960s\u20132015 and its natural and anthropogenic causes. Remote Sens Environ 221:386\u2013404. https:\/\/doi.org\/10.1016\/j.rse.2018.11.038","journal-title":"Remote Sens Environ"},{"key":"734_CR68","doi-asserted-by":"publisher","first-page":"723","DOI":"10.1080\/22797254.2018.1482523","volume":"51","author":"H Zhuang","year":"2018","unstructured":"Zhuang H, Fan H, Deng K, Yu Y (2018) An improved neighborhood-based ratio approach for change detection in SAR images. Eur J Remote Sens 51:723\u2013738. https:\/\/doi.org\/10.1080\/22797254.2018.1482523","journal-title":"Eur J Remote Sens"},{"key":"734_CR69","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1080\/07038992.2020.1740083","volume":"46","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Zhao H (2020) Land\u2013use and land-cover change detection using dynamic time warping\u2013based time series clustering method. Can J Remote Sens 46:67\u201383. https:\/\/doi.org\/10.1080\/07038992.2020.1740083","journal-title":"Can J Remote Sens"}],"container-title":["Earth Science Informatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-021-00734-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s12145-021-00734-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s12145-021-00734-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,2,10]],"date-time":"2022-02-10T02:15:54Z","timestamp":1644459354000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s12145-021-00734-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,9]]},"references-count":69,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,3]]}},"alternative-id":["734"],"URL":"https:\/\/doi.org\/10.1007\/s12145-021-00734-y","relation":{},"ISSN":["1865-0473","1865-0481"],"issn-type":[{"value":"1865-0473","type":"print"},{"value":"1865-0481","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,9]]},"assertion":[{"value":"16 March 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 December 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"9 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}