{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,27]],"date-time":"2025-10-27T16:14:54Z","timestamp":1761581694030,"version":"3.41.0"},"reference-count":25,"publisher":"Springer Science and Business Media LLC","issue":"7","license":[{"start":{"date-parts":[[2018,5,2]],"date-time":"2018-05-02T00:00:00Z","timestamp":1525219200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2018,10]]},"DOI":"10.1007\/s11760-018-1290-0","type":"journal-article","created":{"date-parts":[[2018,5,2]],"date-time":"2018-05-02T02:39:49Z","timestamp":1525228789000},"page":"1361-1367","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["A sparsity-based Bayesian approach for hyperspectral unmixing using normal compositional model"],"prefix":"10.1007","volume":"12","author":[{"given":"F.","family":"Amiri","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"M. H.","family":"Kahaei","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2018,5,2]]},"reference":[{"issue":"1","key":"1290_CR1","doi-asserted-by":"publisher","first-page":"110","DOI":"10.1016\/j.rse.2007.07.028","volume":"113","author":"A Plaza","year":"2009","unstructured":"Plaza, A., Benediktsson, J.A., Boardman, J., Brazile, J., Bruzzone, L., Camps-Valls, G., Chanussot, J., Fauvel, M., Gamba, P., Gualtieri, J., Marconcini, M., Tilton, J.C., Trianni, G.: Recent advances in techniques for hyperspectral image processing. Remote Sens. Environ. 113(1), 110\u2013122 (2009)","journal-title":"Remote Sens. Environ."},{"issue":"1","key":"1290_CR2","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1080\/01431160802304625","volume":"30","author":"B Somers","year":"2009","unstructured":"Somers, B., Delalieux, S., Stuckens, J., Verstraeten, W.W., Coppin, P.: A weighted linear spectral mixture analysis approach to address endmember variability in agricultural production systems. Int. J. Remote Sens. 30(1), 139\u2013147 (2009)","journal-title":"Int. J. Remote Sens."},{"issue":"6","key":"1290_CR3","doi-asserted-by":"publisher","first-page":"1159","DOI":"10.1080\/01431169308904402","volume":"14","author":"JJ Settle","year":"1993","unstructured":"Settle, J.J., Drake, N.A.: Linear mixing and the estimation of ground cover proportions. Int. J. Remote Sens. 14(6), 1159\u20131177 (1993)","journal-title":"Int. J. Remote Sens."},{"issue":"3","key":"1290_CR4","doi-asserted-by":"publisher","first-page":"1144","DOI":"10.1109\/36.843007","volume":"38","author":"CI Chang","year":"2000","unstructured":"Chang, C.I., Heinz, D.C.: Constrained subpixel target detection for remotely sensed imagery. IEEE Trans. Geosci. Remote Sens. 38(3), 1144\u20131159 (2000)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"2\u20133","key":"1290_CR5","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1016\/0034-4257(93)90012-M","volume":"44","author":"G Vane","year":"1993","unstructured":"Vane, G., Green, R., Chrien, T., Enmark, H., Hansen, E., Porter, W.: The airborne visible\/infrared imaging spectrometer (AVIRIS). Remote Sens. Environ. 44(2\u20133), 127\u2013143 (1993)","journal-title":"Remote Sens. Environ."},{"issue":"1","key":"1290_CR6","doi-asserted-by":"publisher","first-page":"44","DOI":"10.1109\/79.974727","volume":"19","author":"N Keshava","year":"2002","unstructured":"Keshava, N., Mustard, J.F.: Spectral unmixing. IEEE Signal Proc. Mag. 19(1), 44\u201357 (2002)","journal-title":"IEEE Signal Proc. Mag."},{"issue":"2","key":"1290_CR7","doi-asserted-by":"publisher","first-page":"1083","DOI":"10.1109\/36.841987","volume":"38","author":"C Bateson","year":"2000","unstructured":"Bateson, C., Asner, G., Wessman, C.: Endmember bundles: a new approach to incorporating endmember variability into spectral mixture analysis. IEEE Trans. Geosci. Remote Sens. 38(2), 1083\u20131094 (2000)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"1290_CR8","doi-asserted-by":"publisher","first-page":"95","DOI":"10.1109\/MSP.2013.2279177","volume":"31","author":"A Zare","year":"2014","unstructured":"Zare, A., Ho, K.C.: Endmember variability in hyperspectral analysis. IEEE Signal Proc. Mag. 31(1), 95\u2013104 (2014)","journal-title":"IEEE Signal Proc. Mag."},{"issue":"11","key":"1290_CR9","doi-asserted-by":"publisher","first-page":"4318","DOI":"10.1109\/TGRS.2011.2166766","volume":"49","author":"F Mianji","year":"2011","unstructured":"Mianji, F., Zhang, Y.: SVM-based unmixing-to-classification conversion for hyperspectral abundance quantification. IEEE Trans. Geosci. Remote Sens. 49(11), 4318\u20134327 (2011)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1290_CR10","doi-asserted-by":"crossref","unstructured":"Stein, D.: Application of the normal compositional model to the analysis of hyperspectral imagery. In: Proceedings of Workshop Advances in Techniques for Analysis Remotely Sensed Data, pp. 44\u201351. Greenbelt, USA (2003)","DOI":"10.1109\/WARSD.2003.1295171"},{"issue":"6","key":"1290_CR11","doi-asserted-by":"publisher","first-page":"1994","DOI":"10.1109\/JSTARS.2014.2330347","volume":"7","author":"X Du","year":"2014","unstructured":"Du, X., Zare, A., Gader, P., Dranishnikov, D.: Spatial and spectral unmixing using the beta compositional model. IEEE J. Sel. Top. Appl. Earth Obs. 7(6), 1994\u20132002 (2014)","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs."},{"issue":"6","key":"1290_CR12","doi-asserted-by":"publisher","first-page":"1403","DOI":"10.1109\/TIP.2010.2042993","volume":"19","author":"O Eches","year":"2010","unstructured":"Eches, O., Dobigeon, N., Mailhes, C., Tourneret, J.Y.: Bayesian estimation of linear mixtures using the normal compositional model. Application to hyperspectral imagery. IEEE Trans. Image Process. 19(6), 1403\u20131413 (2010)","journal-title":"IEEE Trans. Image Process."},{"issue":"3","key":"1290_CR13","doi-asserted-by":"publisher","first-page":"1655","DOI":"10.1109\/TGRS.2012.2207905","volume":"51","author":"A Zare","year":"2013","unstructured":"Zare, A., Gader, P., Casella, G.: Sampling piecewise convex unmixing and endmember extraction. IEEE Trans. Geosci. Remote Sens. 51(3), 1655\u20131665 (2013)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"1290_CR14","doi-asserted-by":"publisher","first-page":"959","DOI":"10.1007\/s11760-015-0753-9","volume":"9","author":"I \u00dclk\u00fc","year":"2015","unstructured":"\u00dclk\u00fc, I., T\u00f6reyin, B.U.: Sparse coding of hyperspectral imagery using online learning. Signal Image Video Proc. 9(4), 959\u2013966 (2015)","journal-title":"Signal Image Video Proc."},{"issue":"2","key":"1290_CR15","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1109\/TSP.2015.2486746","volume":"64","author":"PA Thouvenin","year":"2016","unstructured":"Thouvenin, P.A., Dobigeon, N., Tourneret, J.Y.: Hyperspectral unmixing with spectral variability using a perturbed linear mixing model. IEEE Trans. Signal Proc. 64(2), 525\u2013538 (2016)","journal-title":"IEEE Trans. Signal Proc."},{"issue":"4","key":"1290_CR16","doi-asserted-by":"publisher","first-page":"761","DOI":"10.1007\/s11760-015-0808-y","volume":"10","author":"J Peng","year":"2016","unstructured":"Peng, J., Luo, T.: Sparse matrix transform-based linear discriminant analysis for hyperspectral image classification. Signal Image Video Process. 10(4), 761\u2013768 (2016)","journal-title":"Signal Image Video Process."},{"issue":"5","key":"1290_CR17","doi-asserted-by":"publisher","first-page":"2812","DOI":"10.1109\/TGRS.2015.2506168","volume":"54","author":"T Uezato","year":"2016","unstructured":"Uezato, T., Murphy, R.J., Melkumyan, A., Chlingaryan, A.: A novel spectral unmixing method incorporating spectral variability within endmember classes. IEEE Trans. Geosci. Remote Sens. 54(5), 2812\u20132831 (2016)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1290_CR18","doi-asserted-by":"crossref","unstructured":"Eismann, M.T., Stein, D.: Stochastic mixture modeling in hyperspectral data exploitation: theory and applications, Ch 5. In: Chang, C.I. (ed.) Wiley, New York (2007)","DOI":"10.1002\/9780470124628.ch5"},{"key":"1290_CR19","unstructured":"Guo, Z., Wittman, T., Osher, S.: L1 unmixing and its application to hyperspectral image enhancement. In: Proceedings of the SPIE,7334, pp. 1-9. Orlando, USA (2009)"},{"key":"1290_CR20","doi-asserted-by":"publisher","DOI":"10.1002\/9781119995784","volume-title":"Dirichlet and Related Distributions: Theory, Methods and Applications","author":"KW Ng","year":"2011","unstructured":"Ng, K.W., Tian, G.L., Tang, M.L.: Dirichlet and Related Distributions: Theory, Methods and Applications. Wiley, New York (2011)"},{"key":"1290_CR21","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-4145-2","volume-title":"Monte Carlo Statistical Methods","author":"CP Robert","year":"2004","unstructured":"Robert, C.P., Casella, G.: Monte Carlo Statistical Methods, 2nd edn. Springer, New York (2004)","edition":"2"},{"key":"1290_CR22","unstructured":"http:\/\/speclab.cr.usgs.gov\/spectral-lib.html [Online]. Accessed May 2016"},{"key":"1290_CR23","unstructured":"Swayze, G., Clark, R., Sutley, S., Gallagher, A.: Ground-truthing AVIRIS mineral mapping at Cuprite, Nevada. In: Proceedings of the Summaries 3rd Annual JPL Airborne Geosci. Workshop, pp. 47\u201349 (1992). https:\/\/aviris.jpl.nasa.gov\/data\/free_data.html . Accessed May 2016"},{"issue":"3","key":"1290_CR24","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1109\/36.911111","volume":"39","author":"D Heinz","year":"2001","unstructured":"Heinz, D., Chang, C.I.: Fully constrained least squares linear spectral mixture analysis method for material quantification in hyperspectral imagery. IEEE Trans. Geosci. Remote Sens. 39(3), 529\u2013545 (2001)","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"1290_CR25","unstructured":"Zare, A., Gader, P., Drashnikov, D., Glenn, T.: Beta compositional model for hyperspectral unmixing. In: Proceedings of the 5th Workshop Hyperspectral Image Signal Processing: Evolution Remote Sensing, Gainesville, USA (2013)"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11760-018-1290-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-018-1290-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-018-1290-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T01:29:13Z","timestamp":1751592553000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11760-018-1290-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,5,2]]},"references-count":25,"journal-issue":{"issue":"7","published-print":{"date-parts":[[2018,10]]}},"alternative-id":["1290"],"URL":"https:\/\/doi.org\/10.1007\/s11760-018-1290-0","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2018,5,2]]},"assertion":[{"value":"25 October 2016","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 April 2018","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 April 2018","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 May 2018","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}