{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,25]],"date-time":"2025-03-25T14:13:42Z","timestamp":1742912022624,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030341121"},{"type":"electronic","value":"9783030341138"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-34113-8_26","type":"book-chapter","created":{"date-parts":[[2019,11,27]],"date-time":"2019-11-27T17:03:47Z","timestamp":1574874227000},"page":"305-319","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Modified LDE for Dimensionality Reduction of Hyperspectral Image"],"prefix":"10.1007","author":[{"given":"Lei","family":"He","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongwei","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lina","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,11,28]]},"reference":[{"issue":"6","key":"26_CR1","doi-asserted-by":"publisher","first-page":"6611","DOI":"10.3390\/rs70606611","volume":"7","author":"G Lianru","year":"2015","unstructured":"Lianru, G., Bin, Y., Qian, D., et al.: Adjusted spectral matched filter for target detection in hyperspectral imagery. Remote Sensing 7(6), 6611\u20136634 (2015)","journal-title":"Remote Sensing"},{"issue":"8","key":"26_CR2","doi-asserted-by":"publisher","first-page":"4955","DOI":"10.1109\/TGRS.2013.2286195","volume":"52","author":"L Zhang","year":"2014","unstructured":"Zhang, L., Zhang, L., Tao, D., et al.: Hyperspectral remote sensing image subpixel target detection based on supervised metric learning. IEEE Trans. Geosci. Remote Sens. 52(8), 4955\u20134965 (2014)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"6","key":"26_CR3","doi-asserted-by":"publisher","first-page":"2506","DOI":"10.1109\/JSTARS.2014.2329474","volume":"7","author":"H Onoyama","year":"2014","unstructured":"Onoyama, H., Ryu, C., Suguri, M., et al.: Integrate growing temperature to estimate the nitrogen content of rice plants at the heading stage using hyperspectral imagery. IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing 7(6), 2506\u20132515 (2014)","journal-title":"IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing"},{"issue":"2","key":"26_CR4","doi-asserted-by":"publisher","first-page":"595","DOI":"10.1109\/JSTARS.2015.2471176","volume":"9","author":"G Cheng","year":"2017","unstructured":"Cheng, G., Zhu, F., Xiang, S., et al.: Semisupervised hyperspectral image classification via discriminant analysis and robust regression. IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing 9(2), 595\u2013608 (2017)","journal-title":"IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing"},{"issue":"100","key":"26_CR5","first-page":"513","volume":"87","author":"IT Jolliffe","year":"2002","unstructured":"Jolliffe, I.T.: Principal component analysis. J. Mark. Res. 87(100), 513 (2002)","journal-title":"J. Mark. Res."},{"issue":"3","key":"26_CR6","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1109\/TGRS.2008.2005729","volume":"47","author":"TV Bandos","year":"2009","unstructured":"Bandos, T.V., Bruzzone, L., Camps-Valls, G.: Classification of hyperspectral images with regularized linear discriminant analysis. IEEE Trans. Geosci. Remote Sens. 47(3), 862\u2013873 (2009)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"26_CR7","doi-asserted-by":"crossref","unstructured":"Zhang, X., Liang, Y., Cahill, N.: Using superpixels to improve the efficiency of Laplacian Eigenmap based methods for target detection in hyperspectral imagery. In: Geoscience & Remote Sensing Symposium, IEEE (2016)","DOI":"10.1109\/IGARSS.2016.7730535"},{"key":"26_CR8","doi-asserted-by":"crossref","unstructured":"Wang, M., Yu, J., Niu, L., et al.: Unsupervised feature extraction for hyperspectral images using combined low rank representation and locally linear embedding. In: IEEE ICASSP 2017\u20132017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) - New Orleans, LA, USA, 5 March 2017\u20139 March 2017, pp. 1428\u20131431 (2017)","DOI":"10.1109\/ICASSP.2017.7952392"},{"key":"26_CR9","doi-asserted-by":"crossref","unstructured":"Zhang, M., Jia, P., Shen, Y., et al.: Hyperspectral image classification method based on orthogonal NMF and LPP. In: Instrumentation & Measurement Technology Conference, IEEE (2016)","DOI":"10.1109\/I2MTC.2016.7520353"},{"issue":"1","key":"26_CR10","first-page":"1027","volume":"8","author":"M Sugiyama","year":"2007","unstructured":"Sugiyama, M.: Dimensionality reduction of multimodal labeled data by local fisher discriminant analysis. J. Mach. Learn. Res. 8(1), 1027\u20131061 (2007)","journal-title":"J. Mach. Learn. Res."},{"issue":"4","key":"26_CR11","doi-asserted-by":"publisher","first-page":"1185","DOI":"10.1109\/TGRS.2011.2165957","volume":"50","author":"W Li","year":"2012","unstructured":"Li, W., Prasad, S., Fowler, J.E., et al.: Locality-preserving dimensionality reduction and classification for hyperspectral image analysis. IEEE Trans. Geosci. Remote Sens. 50(4), 1185\u20131198 (2012)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"26_CR12","unstructured":"Chen, H.T., Chang, H.W., Liu, T.L.: Local discriminant embedding and its variants. In: IEEE Computer Society Conference on Computer Vision & Pattern Recognition (2005"},{"issue":"1","key":"26_CR13","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1109\/TPAMI.2007.250598","volume":"29","author":"S Yan","year":"2007","unstructured":"Yan, S., Xu, D., Zhang, B., et al.: Graph embedding: a general framework for dimensionality reduction. IEEE Trans. Pattern Anal. Mach. Intell. 29(1), 40 (2007)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"4","key":"26_CR14","doi-asserted-by":"publisher","first-page":"858","DOI":"10.1109\/TIP.2009.2038764","volume":"19","author":"B Cheng","year":"2010","unstructured":"Cheng, B., Yang, J., Yan, S., et al.: Learning with 1-graph for image analysis. IEEE Trans. Image Process. 19(4), 858\u2013866 (2010)","journal-title":"IEEE Trans. Image Process."},{"issue":"7","key":"26_CR15","doi-asserted-by":"publisher","first-page":"3872","DOI":"10.1109\/TGRS.2013.2277251","volume":"52","author":"NH Ly","year":"2014","unstructured":"Ly, N.H., Du, Q., Fowler, J.E.: Sparse graph-based discriminant analysis for hyperspectral imagery. IEEE Trans. Geosci. Remote Sens. 52(7), 3872\u20133884 (2014)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"7","key":"26_CR16","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1109\/TGRS.2016.2558079","volume":"54","author":"W Li","year":"2016","unstructured":"Li, W., Liu, J., Du, Q.: Sparse and low-rank graph for discriminant analysis of hyperspectral imagery. IEEE Trans. Geosci. Remote Sens. 54(7), 1\u201312 (2016)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"26_CR17","doi-asserted-by":"publisher","first-page":"323","DOI":"10.3390\/rs9040323","volume":"9","author":"F Fubiao","year":"2017","unstructured":"Fubiao, F., Wei, L., Qian, D., et al.: Dimensionality reduction of hyperspectral image with graph-based discriminant analysis considering spectral similarity. Remote Sensing 9(4), 323 (2017)","journal-title":"Remote Sensing"},{"issue":"2","key":"26_CR18","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1109\/LGRS.2017.2786223","volume":"15","author":"YJ Deng","year":"2018","unstructured":"Deng, Y.J., Li, H.C., Pan, L., et al.: Modified tensor locality preserving projection for dimensionality reduction of hyperspectral images. IEEE Geosci. Remote Sens. Lett. 15(2), 277\u2013281 (2018)","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"26_CR19","doi-asserted-by":"crossref","unstructured":"Yang, X., Tu, S., Bai, Y., et al.: Fusion of intensity\/coherent information using region covariance features for unsupervised classification of SAR imagery. In: Geoscience & Remote Sensing Symposium, IEEE (2016)","DOI":"10.1109\/IGARSS.2016.7729238"},{"key":"26_CR20","doi-asserted-by":"crossref","unstructured":"Yang, J., Xing, C., Chen, Y.: Improving the ScSPM model with Log-Euclidean Covariance matrix for scene classification. In: 2016 International Conference on Computer on Information and Telecommunication Systems (CITS), IEEE (2016)","DOI":"10.1109\/CITS.2016.7546458"}],"container-title":["Lecture Notes in Computer Science","Image and Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-34113-8_26","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,1]],"date-time":"2023-09-01T00:05:10Z","timestamp":1693526710000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-34113-8_26"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030341121","9783030341138"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-34113-8_26","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"28 November 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIG","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image and Graphics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Beijing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 August 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 August 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icig2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.csig.org.cn\/detail\/2669","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}