{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T01:33:03Z","timestamp":1773970383858,"version":"3.50.1"},"reference-count":70,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,2,1]],"date-time":"2026-02-01T00:00:00Z","timestamp":1769904000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1803117"],"award-info":[{"award-number":["U1803117"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100019176","name":"Mineral Resources","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100019176","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018537","name":"National Science and Technology Major Project","doi-asserted-by":"publisher","award":["2025ZD1008600"],"award-info":[{"award-number":["2025ZD1008600"]}],"id":[{"id":"10.13039\/501100018537","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Knowledge-Based Systems"],"published-print":{"date-parts":[[2026,2]]},"DOI":"10.1016\/j.knosys.2025.115243","type":"journal-article","created":{"date-parts":[[2025,12,30]],"date-time":"2025-12-30T16:58:11Z","timestamp":1767113891000},"page":"115243","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["Sparse unmixing of hyperspectral images based on multi-scale superpixel-guided low-rank representation"],"prefix":"10.1016","volume":"335","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-7651-5950","authenticated-orcid":false,"given":"Taowei","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6272-1618","authenticated-orcid":false,"given":"Weitao","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8592-7689","authenticated-orcid":false,"given":"Xuwen","family":"Qin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2510-2711","authenticated-orcid":false,"given":"Xinfeng","family":"Dong","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6830-3145","authenticated-orcid":false,"given":"Fuping","family":"Gan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"issue":"2","key":"10.1016\/j.knosys.2025.115243_bib0001","doi-asserted-by":"crossref","first-page":"6","DOI":"10.1109\/MGRS.2013.2244672","article-title":"Hyperspectral remote sensing data analysis and future challenges","volume":"1","author":"Bioucas-Dias","year":"2013","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"10.1016\/j.knosys.2025.115243_bib0002","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113408","article-title":"A non-local sparse unmixing based hyperspectral change detection with unsupervised deep clustering","volume":"317","author":"Gao","year":"2025","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.knosys.2025.115243_bib0003","doi-asserted-by":"crossref","first-page":"6945","DOI":"10.1109\/JSTARS.2024.3377104","article-title":"Design and verification of a low-cost multispectral camera for precision agriculture application","volume":"17","author":"Barjaktarovic","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0004","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2020.106657","article-title":"Endmember independence constrained hyperspectral unmixing via nonnegative tensor factorization","volume":"216","author":"Wang","year":"2021","journal-title":"Knowl. Based Syst."},{"issue":"9","key":"10.1016\/j.knosys.2025.115243_bib0005","doi-asserted-by":"crossref","first-page":"9104","DOI":"10.3390\/rs6099104","article-title":"Mapping layers of clay in a vertical geological surface using hyperspectral imagery: variability in parameters of swir absorption features under different conditions of illumination","volume":"6","author":"Murphy","year":"2014","journal-title":"Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0006","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2024.3386402","article-title":"A novel framework for solar panel segmentation from remote sensing images: utilizing chebyshev transformer and hyperspectral decomposition","volume":"62","author":"Gasparyan","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"2","key":"10.1016\/j.knosys.2025.115243_bib0007","doi-asserted-by":"crossref","first-page":"1922","DOI":"10.1109\/TETCI.2024.3359070","article-title":"Sparse hyperspectral unmixing with preference-based evolutionary multiobjective multitasking optimization","volume":"8","author":"Li","year":"2024","journal-title":"IEEE Trans. Emerging Top. Comput. Intell."},{"issue":"2","key":"10.1016\/j.knosys.2025.115243_bib0008","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1109\/MSP.2022.3208987","article-title":"Integration of physics-based and data-driven models for hyperspectral image unmixing: a summary of current methods","volume":"40","author":"Chen","year":"2023","journal-title":"IEEE Signal Process. Mag."},{"key":"10.1016\/j.knosys.2025.115243_bib0009","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.111306","article-title":"Evolutionary multitasking cooperative transfer for multiobjective hyperspectral sparse unmixing","volume":"285","author":"Li","year":"2024","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.knosys.2025.115243_bib0010","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2019.104898","article-title":"Cauchy sparse nmf with manifold regularization: a robust method for hyperspectral unmixing","volume":"184","author":"Wang","year":"2019","journal-title":"Knowl. Based Syst."},{"issue":"2","key":"10.1016\/j.knosys.2025.115243_bib0011","doi-asserted-by":"crossref","first-page":"354","DOI":"10.1109\/JSTARS.2012.2194696","article-title":"Hyperspectral unmixing overview: geometrical, statistical, and sparse regression-based approaches","volume":"5","author":"Bioucas-Dias","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"issue":"3","key":"10.1016\/j.knosys.2025.115243_bib0012","doi-asserted-by":"crossref","first-page":"2391","DOI":"10.1109\/TGRS.2020.3006109","article-title":"Spectral-spatial joint sparse nmf for hyperspectral unmixing","volume":"59","author":"Dong","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"10.1016\/j.knosys.2025.115243_bib0013","doi-asserted-by":"crossref","first-page":"2419","DOI":"10.1109\/TGRS.2018.2873326","article-title":"Joint-sparse-blocks and low-rank representation for hyperspectral unmixing","volume":"57","author":"Huang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0014","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1109\/JSTARS.2021.3132164","article-title":"Robust double spatial regularization sparse hyperspectral unmixing","volume":"14","author":"Li","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0015","doi-asserted-by":"crossref","first-page":"1269","DOI":"10.1109\/JSTARS.2023.3337130","article-title":"Robust multiscale spectral-spatial regularized sparse unmixing for hyperspectral imagery","volume":"17","author":"Wang","year":"2024","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"issue":"2","key":"10.1016\/j.knosys.2025.115243_bib0016","doi-asserted-by":"crossref","first-page":"1453","DOI":"10.1109\/TGRS.2020.2999936","article-title":"Correntropy-based spatial-spectral robust sparsity-regularized hyperspectral unmixing","volume":"59","author":"Li","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"10.1016\/j.knosys.2025.115243_bib0017","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1109\/MGRS.2021.3071158","article-title":"Spectral variability in hyperspectral data unmixing: a comprehensive review","volume":"9","author":"Borsoi","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"issue":"10","key":"10.1016\/j.knosys.2025.115243_bib0018","doi-asserted-by":"crossref","first-page":"7418","DOI":"10.1109\/TGRS.2020.2982490","article-title":"Spectral mixture model inspired network architectures for hyperspectral unmixing","volume":"58","author":"Qian","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0019","doi-asserted-by":"crossref","first-page":"4414","DOI":"10.1109\/JSTARS.2022.3175257","article-title":"Hyperspectral unmixing based on nonnegative matrix factorization: a comprehensive review","volume":"15","author":"Feng","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0020","first-page":"1","article-title":"MiSiCNet: minimum simplex convolutional network for deep hyperspectral unmixing","volume":"60","author":"Rasti","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"7","key":"10.1016\/j.knosys.2025.115243_bib0021","doi-asserted-by":"crossref","first-page":"2744","DOI":"10.1109\/TGRS.2011.2174443","article-title":"A new minimum-volume enclosing algorithm for endmember identification and abundance estimation in hyperspectral data","volume":"50","author":"Hendrix","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"10.1016\/j.knosys.2025.115243_bib0022","doi-asserted-by":"crossref","first-page":"898","DOI":"10.1109\/TGRS.2005.844293","article-title":"Vertex component analysis: a fast algorithm to unmix hyperspectral data","volume":"43","author":"Nascimento","year":"2005","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"3","key":"10.1016\/j.knosys.2025.115243_bib0023","doi-asserted-by":"crossref","first-page":"1776","DOI":"10.1109\/TGRS.2016.2633279","article-title":"Matrix-vector nonnegative tensor factorization for blind unmixing of hyperspectral imagery","volume":"55","author":"Qian","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0024","first-page":"1","article-title":"A coarse-to-fine scheme for unsupervised nonlinear hyperspectral unmixing based on an extended multilinear mixing model","volume":"61","author":"Li","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0025","first-page":"1","article-title":"Superpixel-based graph laplacian regularization for sparse hyperspectral unmixing","volume":"19","author":"Ince","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"10.1016\/j.knosys.2025.115243_bib0026","doi-asserted-by":"crossref","unstructured":"Y. Liang, H. Zheng, G. Yang, Q. Du, H. Su, Superpixel-based weighted sparse regression and spectral similarity constrained for hyperspectral unmixing, IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens.2023, pp. 6825\u20136842.","DOI":"10.1109\/JSTARS.2023.3298491"},{"issue":"7","key":"10.1016\/j.knosys.2025.115243_bib0027","doi-asserted-by":"crossref","first-page":"1046","DOI":"10.3390\/rs10071046","article-title":"Double reweighted sparse regression and graph regularization for hyperspectral unmixing","volume":"10","author":"Wang","year":"2018","journal-title":"Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0028","first-page":"1","article-title":"Spatial-spectral multiscale sparse unmixing for hyperspectral images","volume":"20","author":"Ince","year":"2023","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"5","key":"10.1016\/j.knosys.2025.115243_bib0029","doi-asserted-by":"crossref","first-page":"1545","DOI":"10.1109\/JSTARS.2012.2199282","article-title":"Enhancing spectral unmixing by local neighborhood weights","volume":"5","author":"Liu","year":"2012","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"issue":"6","key":"10.1016\/j.knosys.2025.115243_bib0030","doi-asserted-by":"crossref","first-page":"2014","DOI":"10.1109\/TGRS.2010.2098413","article-title":"Sparse unmixing of hyperspectral data","volume":"49","author":"Iordache","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"10.1016\/j.knosys.2025.115243_bib0031","doi-asserted-by":"crossref","first-page":"3309","DOI":"10.1109\/TGRS.2020.3007945","article-title":"Hyperspectral image restoration via global \u21131\/2 spatial-spectral total variation regularized local low-rank tensor recovery","volume":"59","author":"Zeng","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"11","key":"10.1016\/j.knosys.2025.115243_bib0032","doi-asserted-by":"crossref","first-page":"6371","DOI":"10.1109\/TGRS.2016.2582824","article-title":"Blind hyperspectral unmixing using total variation and \u2113q sparse regularization","volume":"54","author":"Sigurdsson","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"7","key":"10.1016\/j.knosys.2025.115243_bib0033","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.1109\/LGRS.2017.2700542","article-title":"Hyperspectral unmixing using double reweighted sparse regression and total variation","volume":"14","author":"Wang","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"1","key":"10.1016\/j.knosys.2025.115243_bib0034","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1109\/TGRS.2013.2240001","article-title":"Collaborative sparse regression for hyperspectral unmixing","volume":"52","author":"Iordache","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"4","key":"10.1016\/j.knosys.2025.115243_bib0035","doi-asserted-by":"crossref","first-page":"1022","DOI":"10.1109\/JSTARS.2018.2805779","article-title":"Group low-rank nonnegative matrix factorization with semantic regularizer for hyperspectral unmixing","volume":"11","author":"Wang","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"issue":"2","key":"10.1016\/j.knosys.2025.115243_bib0036","doi-asserted-by":"crossref","first-page":"339","DOI":"10.3390\/rs10020339","article-title":"Hyperspectral unmixing via low-rank representation with space consistency constraint and spectral library pruning","volume":"10","author":"Zhang","year":"2018","journal-title":"Remote Sens."},{"issue":"10","key":"10.1016\/j.knosys.2025.115243_bib0037","doi-asserted-by":"crossref","first-page":"7756","DOI":"10.1109\/TGRS.2019.2916296","article-title":"Local spectral similarity preserving regularized robust sparse hyperspectral unmixing","volume":"57","author":"Li","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0038","first-page":"1","article-title":"Spectral-spatial anti-interference nmf for hyperspectral unmixing","volume":"61","author":"Yang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"12","key":"10.1016\/j.knosys.2025.115243_bib0039","doi-asserted-by":"crossref","first-page":"8766","DOI":"10.1109\/TGRS.2020.2990476","article-title":"Spectral-spatial-weighted multiview collaborative sparse unmixing for hyperspectral images","volume":"58","author":"Qi","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0040","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2023.111190","article-title":"\u201cS2eft: spectral-spatial-elevation fusion transformer for hyperspectral image and lidar classification","volume":"283","author":"Feng","year":"2024","journal-title":"Knowl. Based Syst."},{"issue":"11","key":"10.1016\/j.knosys.2025.115243_bib0041","doi-asserted-by":"crossref","first-page":"4484","DOI":"10.1109\/TGRS.2012.2191590","article-title":"Total variation spatial regularization for sparse hyperspectral unmixing","volume":"50","author":"Iordache","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"6","key":"10.1016\/j.knosys.2025.115243_bib0042","doi-asserted-by":"crossref","first-page":"3265","DOI":"10.1109\/TGRS.2018.2797200","article-title":"Spectral-spatial weighted sparse regression for hyperspectral image unmixing","volume":"56","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0043","first-page":"1","article-title":"Stationary wavelet convolutional network with generative feature learning for hyperspectral unmixing","volume":"63","author":"Xu","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0044","first-page":"1","article-title":"Multiscale spatial graph-regularized hierarchical sparse unmixing based on the framelet transform","volume":"63","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0045","first-page":"1","article-title":"Unrolling nonnegative matrix factorization with group sparsity for blind hyperspectral unmixing","volume":"61","author":"Cui","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0046","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2024.112087","article-title":"Graph feature fusion driven by deep autoencoder for advanced hyperspectral image unmixing","volume":"299","author":"Hanachi","year":"2024","journal-title":"Knowl. Based Syst."},{"issue":"4","key":"10.1016\/j.knosys.2025.115243_bib0047","doi-asserted-by":"crossref","first-page":"598","DOI":"10.1109\/LGRS.2018.2878394","article-title":"A fast multiscale spatial regularization for sparse hyperspectral unmixing","volume":"16","author":"Borsoi","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"10.1016\/j.knosys.2025.115243_bib0048","first-page":"1","article-title":"Spectral reweighting and spectral similarity weighting for sparse hyperspectral unmixing","volume":"19","author":"Zhang","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"10.1016\/j.knosys.2025.115243_bib0049","first-page":"1","article-title":"Sparse unmixing of hyperspectral images with noise reduction using spatial filtering","volume":"74","author":"Zhang","year":"2025","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.knosys.2025.115243_bib0050","first-page":"1","article-title":"Double spatial graph laplacian regularization for sparse unmixing","volume":"19","author":"Ince","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"10.1016\/j.knosys.2025.115243_bib0051","first-page":"1","article-title":"Local spectral similarity-guided sparse unmixing of hyperspectral images with spatial graph regularization","volume":"61","author":"Liang","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0052","doi-asserted-by":"crossref","unstructured":"S. Zhang, J. Zheng, Y. Liu, F. Li, C. Deng, A. Plaza, L. Liang, Z. He, S. Wang, Spatial structural priors for sparse unmixing of remotely sensed hyperspectral images, 2025, pp. 1\u201319.","DOI":"10.1109\/JSTARS.2025.3624109"},{"key":"10.1016\/j.knosys.2025.115243_bib0053","first-page":"1","article-title":"Superpixel-based graph laplacian regularized and weighted robust sparse unmixing","volume":"62","author":"Zou","year":"2024","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"10.1016\/j.knosys.2025.115243_bib0054","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1109\/MGRS.2021.3075491","article-title":"Low-rank and sparse representation for hyperspectral image processing: a review","volume":"10","author":"Peng","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"10.1016\/j.knosys.2025.115243_bib0055","doi-asserted-by":"crossref","first-page":"7741","DOI":"10.1109\/JSTARS.2022.3199885","article-title":"Local low-rank approximation with superpixel-guided locality preserving graph for hyperspectral image classification","volume":"15","author":"Yang","year":"2022","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0056","doi-asserted-by":"crossref","first-page":"6119","DOI":"10.1109\/JSTARS.2021.3086631","article-title":"Hyperspectral sparse unmixing with spectral-spatial low-rank constraint","volume":"14","author":"Li","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0057","first-page":"1","article-title":"Superpixel-based collaborative and low-rank regularization for sparse hyperspectral unmixing","volume":"60","author":"Chen","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0058","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1109\/JSTARS.2021.3133428","article-title":"Superpixel-based weighted collaborative sparse regression and reweighted low-rank representation for hyperspectral image unmixing","volume":"15","author":"Su","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0059","first-page":"1","article-title":"Reweighted low-rank and joint-sparse unmixing with library pruning","volume":"60","author":"Zhang","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0060","first-page":"1","article-title":"Efficient hyperspectral sparse regression unmixing with multilayers","volume":"61","author":"Shen","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"issue":"1","key":"10.1016\/j.knosys.2025.115243_bib0061","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1109\/TGRS.2020.2994260","article-title":"Superpixel-based reweighted low-rank and total variation sparse unmixing for hyperspectral remote sensing imagery","volume":"59","author":"Li","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0062","first-page":"1","article-title":"Double-weighted spatial low-rank and superpixel-guided adaptive graph laplacian regularization for sparse hyperspectral unmixing","volume":"74","author":"Wang","year":"2025","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"10.1016\/j.knosys.2025.115243_bib0063","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.114586","article-title":"A nonlocal superpatch-based reweighted low-rank representation method for hyperspectral unmixing","volume":"330","author":"Zhao","year":"2025","journal-title":"Knowl. Based Syst."},{"key":"10.1016\/j.knosys.2025.115243_bib0064","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113428","article-title":"Dual-stream autoencoder for channel-level multi-scale feature extraction in hyperspectral unmixing","volume":"317","author":"Gan","year":"2025","journal-title":"Knowl. Based Syst."},{"issue":"9","key":"10.1016\/j.knosys.2025.115243_bib0065","doi-asserted-by":"crossref","first-page":"5495","DOI":"10.1109\/TGRS.2018.2818703","article-title":"Collaborative sparse hyperspectral unmixing using \u21130 norm","volume":"56","author":"Shi","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"10.1016\/j.knosys.2025.115243_bib0066","article-title":"A two-step iterative algorithm for sparse hyperspectral unmixing via total variation","volume":"401","author":"Wang","year":"2021","journal-title":"Appl. Math. Comput."},{"key":"10.1016\/j.knosys.2025.115243_bib0067","doi-asserted-by":"crossref","first-page":"1754","DOI":"10.1109\/JSTARS.2020.3048820","article-title":"Sparse and low-rank constrained tensor factorization for hyperspectral image unmixing","volume":"14","author":"Zheng","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"issue":"8","key":"10.1016\/j.knosys.2025.115243_bib0068","doi-asserted-by":"crossref","first-page":"1440","DOI":"10.1109\/LGRS.2019.2945546","article-title":"Semisupervised classification based on slic segmentation for hyperspectral image","volume":"17","author":"Zhang","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"issue":"10","key":"10.1016\/j.knosys.2025.115243_bib0069","doi-asserted-by":"crossref","first-page":"1767","DOI":"10.1109\/LGRS.2019.2954335","article-title":"Combined nonlocal spatial information and spatial group sparsity in nmf for hyperspectral unmixing","volume":"17","author":"Yang","year":"2019","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"10.1016\/j.knosys.2025.115243_bib0070","doi-asserted-by":"crossref","DOI":"10.1016\/j.knosys.2025.113003","article-title":"A multi-scale semantically enriched feature pyramid network with enhanced focal loss for small-object detection","volume":"310","author":"Kiobya","year":"2025","journal-title":"Knowl. Based Syst."}],"container-title":["Knowledge-Based Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705125022774?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0950705125022774?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,3,19]],"date-time":"2026-03-19T23:58:31Z","timestamp":1773964711000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0950705125022774"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,2]]},"references-count":70,"alternative-id":["S0950705125022774"],"URL":"https:\/\/doi.org\/10.1016\/j.knosys.2025.115243","relation":{},"ISSN":["0950-7051"],"issn-type":[{"value":"0950-7051","type":"print"}],"subject":[],"published":{"date-parts":[[2026,2]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Sparse unmixing of hyperspectral images based on multi-scale superpixel-guided low-rank representation","name":"articletitle","label":"Article Title"},{"value":"Knowledge-Based Systems","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.knosys.2025.115243","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2025 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}],"article-number":"115243"}}