{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T22:14:06Z","timestamp":1769552046923,"version":"3.49.0"},"reference-count":45,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2017,3,26]],"date-time":"2017-03-26T00:00:00Z","timestamp":1490486400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Cloud detection of remote sensing imagery is quite challenging due to the influence of complicated underlying surfaces and the variety of cloud types. Currently, most of the methods mainly rely on prior knowledge to extract features artificially for cloud detection. However, these features may not be able to accurately represent the cloud characteristics under complex environment. In this paper, we adopt an innovative model named Fuzzy Autoencode Model (FAEM) to integrate the feature learning ability of stacked autoencode networks and the detection ability of fuzzy function for highly accurate cloud detection on remote sensing imagery. Our proposed method begins by selecting and fusing spectral, texture, and structure information. Thereafter, the proposed technique established a FAEM to learn the deep discriminative features from a great deal of selected information. Finally, the learned features are mapped to the corresponding cloud density map with a fuzzy function. To demonstrate the effectiveness of the proposed method, 172 Landsat ETM+ images and 25 GF-1 images with different spatial resolutions are used in this paper. For the convenience of accuracy assessment, ground truth data are manually outlined. Results show that the average RER (ratio of right rate and error rate) on Landsat images is greater than 29, while the average RER of Support Vector Machine (SVM) is 21.8 and Random Forest (RF) is 23. The results on GF-1 images exhibit similar performance as Landsat images with the average RER of 25.9, which is much higher than the results of SVM and RF. Compared to traditional methods, our technique has attained higher average cloud detection accuracy for either different spatial resolutions or various land surfaces.<\/jats:p>","DOI":"10.3390\/rs9040311","type":"journal-article","created":{"date-parts":[[2017,3,27]],"date-time":"2017-03-27T10:49:10Z","timestamp":1490611750000},"page":"311","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":48,"title":["Fuzzy AutoEncode Based Cloud Detection for Remote Sensing Imagery"],"prefix":"10.3390","volume":"9","author":[{"given":"Zhenfeng","family":"Shao","sequence":"first","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center for Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China"}]},{"given":"Juan","family":"Deng","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center for Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center for Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China"}]},{"given":"Yewen","family":"Fan","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Collaborative Innovation Center for Geospatial Technology, 129 Luoyu Road, Wuhan 430079, China"}]},{"given":"Neema","family":"Sumari","sequence":"additional","affiliation":[{"name":"Department of Informatics, Fuculty of Science, Sokoine University of Agriculture (SUA), P.O. Box 3038, Morogoro, Tanzania"}]},{"given":"Qimin","family":"Cheng","sequence":"additional","affiliation":[{"name":"School of Electronics Information and Communications, Huazhong University of Science and Technology, 1037 Luoyu Road, Wuhan 430074, China"}]}],"member":"1968","published-online":{"date-parts":[[2017,3,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.rse.2016.03.034","article-title":"An empirical and radiative transfer model based algorithm to remove thin clouds in visible bands","volume":"179","author":"Lv","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.rse.2016.05.010","article-title":"Global snow cover estimation with microwave brightness temperature measurements and one-class in situ observations","volume":"182","author":"Xu","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1016\/j.rse.2014.12.014","article-title":"Improvement and expansion of the fmask algorithm: Cloud, cloud shadow, and snow detection for landsats 4\u20137, 8, and sentinel 2 images","volume":"159","author":"Zhu","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_4","unstructured":"Bian, J.H., Li, A.N., Jin, H.A., Zhao, W., Lei, G.B., and Huang, C.Q. (2014, January 13\u201318). Multi-temporal cloud and snow detection algorithm for the hj-1a\/b ccd imagery of china. Proceedings of the 2014 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Quebec City, QC, Canada."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1747","DOI":"10.1016\/j.rse.2010.03.002","article-title":"A multi-temporal method for cloud detection, applied to formosat-2, ven\u00b5s, landsat and sentinel-2 images","volume":"114","author":"Hagolle","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1080\/17538947.2013.833313","article-title":"A cloud detection method based on a time series of modis surface reflectance images","volume":"6","author":"Tang","year":"2013","journal-title":"Int. J. Digit. Earth"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1540","DOI":"10.1080\/01431161.2012.720045","article-title":"Automated cloud and shadow detection and filling using two-date landsat imagery in the USA","volume":"34","author":"Jin","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"50","DOI":"10.1016\/j.rse.2013.02.019","article-title":"Cloud and cloud shadow screening across queensland, australia: An automated method for landsat tm\/etm plus time series","volume":"134","author":"Goodwin","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1016\/j.rse.2014.06.012","article-title":"Automated cloud, cloud shadow, and snow detection in multitemporal landsat data: An algorithm designed specifically for monitoring land cover change","volume":"152","author":"Zhu","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1713","DOI":"10.1080\/01431161003621619","article-title":"An optimal image transform for threshold-based cloud detection using heteroscedastic discriminant analysis","volume":"32","author":"Marais","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Shao, Z., Hou, J., Jiang, M., and Zhou, X. (2014). Cloud detection in landsat imagery for antarctic region using multispectral thresholds. SPIE Asia-Pac. Remote Sens. Int. Soc. Opt. Photonics.","DOI":"10.1117\/12.2070635"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2713","DOI":"10.5194\/amt-6-2713-2013","article-title":"A threshold-based cloud mask for the high-resolution visible channel of meteosat second generation seviri","volume":"6","author":"Bley","year":"2013","journal-title":"Atmos. Meas. Tech."},{"key":"ref_13","unstructured":"Zhu, T.T., Wei, H.K., Zhang, C., Zhang, K.J., and Liu, T.H. (2015, January 28\u201330). A local threshold algorithm for cloud detection on ground-based cloud images. Proceedings of the 34th Chinese Control Conference, Hangzhou, China."},{"key":"ref_14","first-page":"348","article-title":"Landsat 7 automatic cloud cover assessment","volume":"4049","author":"Irish","year":"2000","journal-title":"Proc. SPIE Int. Soc. Opt. Eng."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1016\/j.rse.2011.10.028","article-title":"Object-based cloud and cloud shadow detection in landsat imagery","volume":"118","author":"Zhu","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"7264","DOI":"10.1109\/TGRS.2014.2310240","article-title":"Cloud detection of rgb color aerial photographs by progressive refinement scheme","volume":"52","author":"Qing","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Tan, K., Zhang, Y., and Tong, X. (2016). Cloud extraction from chinese high resolution satellite imagery by probabilistic latent semantic analysis and object-based machine learning. Remote Sens., 8.","DOI":"10.3390\/rs8110963"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/j.rse.2004.03.007","article-title":"Cloud detection in landsat imagery of ice sheets using shadow matching technique and automatic normalized difference snow index threshold value decision","volume":"91","author":"Choi","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"9365","DOI":"10.1080\/01431161.2011.556679","article-title":"Sand and dust storm detection over desert regions in china with modis measurements","volume":"32","author":"Xu","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Surya, S.R., and Simon, P. (2013, January 15\u201317). Automatic cloud detection using spectral rationing and fuzzy clustering. Proceedings of the 2013 Second International Conference on Advanced Computing, Networking and Security (Adcons 2013), Mangalore, India.","DOI":"10.1109\/ADCONS.2013.44"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2490","DOI":"10.1109\/36.964986","article-title":"Atmospheric correction of landsat etm+ land surface imagery\u2014Part I: Methods","volume":"39","author":"Liang","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_22","first-page":"89210G","article-title":"Cloud detection based on decision tree over tibetan plateau with modis data","volume":"8921","author":"Xu","year":"2013","journal-title":"Proc. SPIE Int. Soc. Opt. Eng."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Ren, R.Z., Gu, L.J., and Wang, H.F. (2012, January 23\u201325). Clouds and clouds shadows detection and matching in modis multispectral satellite images. Proceedings of the 2012 International Conference on Industrial Control and Electronics Engineering (ICICEE), Xi\u2019an, China.","DOI":"10.1109\/ICICEE.2012.27"},{"key":"ref_24","first-page":"89210N","article-title":"Cloud and shadow detection and removal for landsat-8 data","volume":"8921","author":"Kong","year":"8921","journal-title":"Proc. SPIE Int. Soc. Opt. Eng."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"88900J","DOI":"10.1117\/12.2025238","article-title":"Automated cloud classification using a ground based infra-red camera and texture analysis techniques","volume":"8890","author":"Rumi","year":"2013","journal-title":"SPIE Remote Sens. Int. Soc. Opt. Photonics"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"410","DOI":"10.1175\/2010JTECHA1385.1","article-title":"Cloud classification based on structure features of infrared images","volume":"28","author":"Liu","year":"2011","journal-title":"J. Atmos. Ocean. Technol."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"892104","DOI":"10.1117\/12.2033522","article-title":"A cloud detection algorithm using edge detection and information entropy over urban area","volume":"8921","author":"Zheng","year":"2013","journal-title":"Eighth Int. Symp. Multispectr. Image Process. Pattern Recognit. Int. Soc. Opt. Photonics"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"776","DOI":"10.3390\/rs6010776","article-title":"Cloud and cloud-shadow detection in spot5 hrg imagery with automated morphological feature extraction","volume":"6","author":"Fisher","year":"2014","journal-title":"Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1109\/LGRS.2011.2170953","article-title":"Thin cloud detection of all-sky images using markov random fields","volume":"9","author":"Li","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1109\/LGRS.2014.2356616","article-title":"Neural networks and support vectormachine algorithms for automatic cloud classification of whole-sky ground-based images","volume":"12","author":"Alireza","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Latry, C., and Panem, C. (2007). Cloud detection with svm technique. IEEE Trans. Geosci. Remote Sens., 448\u2013451.","DOI":"10.1109\/IGARSS.2007.4422827"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1760","DOI":"10.1109\/LGRS.2015.2424531","article-title":"Automatic recognition of cloud images by using visual saliency features","volume":"12","author":"Xiangyun","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"012026","DOI":"10.1088\/1755-1315\/18\/1\/012026","article-title":"A new method of cloud detection based on cascaded adaboost","volume":"18","author":"Ma","year":"2014","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_34","unstructured":"GF-1 Images (2016, August 08). Geospatial Data Cloud. Available online: http:\/\/www.gscloud.cn\/."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Bai, T., Li, D.R., Sun, K.M., Chen, Y.P., and Li, W.Z. (2016). Cloud detection for high-resolution satellite imagery using machine learning and multi-feature fusion. Remote Sens., 8.","DOI":"10.3390\/rs8090715"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1016\/j.rse.2013.01.019","article-title":"Generation of new cloud masks from modis land surface reflectance products","volume":"133","author":"Liu","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4206","DOI":"10.1109\/JSTARS.2015.2438015","article-title":"Scene learning for cloud detection on remote-sensing images","volume":"8","author":"An","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.neucom.2014.09.102","article-title":"A cloud image detection method based on svm vector machine","volume":"169","author":"Li","year":"2015","journal-title":"Neurocomputing"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1061","DOI":"10.1109\/LGRS.2014.2377722","article-title":"Impacts of feature normalization on optical and sar data fusion for land use\/land cover classification","volume":"12","author":"Zhang","year":"2015","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1007\/s11263-006-4331-z","article-title":"Structure-texture image decomposition\u2014modeling, algorithms, and parameter selection","volume":"67","author":"Aujol","year":"2006","journal-title":"Int. J. Comput. Vis."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"8","DOI":"10.1109\/LGRS.2014.2322953","article-title":"Object classification via feature fusion based marginalized kernels","volume":"12","author":"Xiao","year":"2015","journal-title":"IEEE Geoscie. Remote Sens. Lett."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"4197","DOI":"10.1109\/JSTARS.2015.2431676","article-title":"Bag-of-words and object-based classification for cloud extraction from satellite imagery","volume":"8","author":"Yuan","year":"2015","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"601","DOI":"10.1080\/2150704X.2014.942921","article-title":"Automatic cloud detection for high spatial resolution multi-temporal images","volume":"5","author":"Han","year":"2014","journal-title":"Remote Sens. Lett."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1016\/j.isprsjprs.2011.03.005","article-title":"A cloud mask methodology for high resolution remote sensing data combining information from high and medium resolution optical sensors","volume":"66","author":"Sedano","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_45","first-page":"891907","article-title":"Cloud detection based on HSI color space and SWT from high resolution color remote sensing imagery","volume":"8919","author":"Chen","year":"2013","journal-title":"Proc. SPIE Int. Soc. Opt. Eng."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/4\/311\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:31:19Z","timestamp":1760207479000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/4\/311"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,3,26]]},"references-count":45,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2017,4]]}},"alternative-id":["rs9040311"],"URL":"https:\/\/doi.org\/10.3390\/rs9040311","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,3,26]]}}}