{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T07:37:46Z","timestamp":1773128266072,"version":"3.50.1"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T00:00:00Z","timestamp":1768953600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T00:00:00Z","timestamp":1768953600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["Nos.12371308"],"award-info":[{"award-number":["Nos.12371308"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Machine Vision and Applications"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1007\/s00138-025-01785-7","type":"journal-article","created":{"date-parts":[[2026,1,21]],"date-time":"2026-01-21T16:42:10Z","timestamp":1769013730000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A general two-stage framework of tensor low-rank representation for enhanced image denoising and clustering"],"prefix":"10.1007","volume":"37","author":[{"given":"Yiqi","family":"Wang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Weidong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Boyuan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Runze","family":"Fang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yali","family":"Fan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yan","family":"Song","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,1,21]]},"reference":[{"key":"1785_CR1","doi-asserted-by":"publisher","first-page":"3397","DOI":"10.1109\/TIP.2023.3284673","volume":"32","author":"L Feng","year":"2023","unstructured":"Feng, L., Zhu, C., Long, Z., Liu, J., Liu, Y.: Multiplex transformed tensor decomposition for multidimensional image recovery. IEEE Trans. Image Process. 32, 3397\u20133412 (2023). https:\/\/doi.org\/10.1109\/TIP.2023.3284673","journal-title":"IEEE Trans. Image Process."},{"key":"1785_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2023.109121","volume":"213","author":"S Ahmadi-Asl","year":"2023","unstructured":"Ahmadi-Asl, S., Asante-Mensah, M.G., Cichocki, A., Phan, A.H., Oseledets, I., Wang, J.: Fast cross tensor approximation for image and video completion. Signal Process. 213, 109121 (2023). https:\/\/doi.org\/10.1016\/j.sigpro.2023.109121. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0165168423001950)","journal-title":"Signal Process."},{"key":"1785_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2023.110812","volume":"277","author":"Q Jiang","year":"2023","unstructured":"Jiang, Q., Zhao, X.L., Lin, J., Fan, Y.R., Peng, J., Wu, G.C.: Superpixel-based robust tensor low-rank approximation for multimedia data recovery. Knowl.-Based Syst. 277, 110812 (2023). https:\/\/doi.org\/10.1016\/j.knosys.2023.110812. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0950705123005622)","journal-title":"Knowl.-Based Syst."},{"key":"1785_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109343","volume":"137","author":"Q Yu","year":"2023","unstructured":"Yu, Q., Yang, M.: Low-rank tensor recovery via non-convex regularization, structured factorization and spatio-temporal characteristics. Pattern Recogn. 137, 109343 (2023). https:\/\/doi.org\/10.1016\/j.patcog.2023.109343. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0031320323000444)","journal-title":"Pattern Recogn."},{"issue":"7","key":"1785_CR5","doi-asserted-by":"publisher","first-page":"8839","DOI":"10.1109\/TNNLS.2022.3215983","volume":"35","author":"JH Yang","year":"2024","unstructured":"Yang, J.H., Chen, C., Dai, H.N., Ding, M., Wu, Z.B., Zheng, Z.: Robust corrupted data recovery and clustering via generalized transformed tensor low-rank representation. IEEE Trans. Neural Netw. Learn. Syst. 35(7), 8839\u20138853 (2024). https:\/\/doi.org\/10.1109\/TNNLS.2022.3215983","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"1785_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2025.129138","volume":"296","author":"W Zhang","year":"2026","unstructured":"Zhang, W., Fan, Y., Song, Y.: Sparsity enhanced tensor denoising based on weighted noise-free and noise estimation via discrete cosine transform. Expert Syst. Appl. 296, 129138 (2026). https:\/\/doi.org\/10.1016\/j.eswa.2025.129138. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0957417425027551)","journal-title":"Expert Syst. Appl."},{"issue":"4","key":"1785_CR7","doi-asserted-by":"publisher","first-page":"925","DOI":"10.1109\/TPAMI.2019.2891760","volume":"42","author":"C Lu","year":"2020","unstructured":"Lu, C., Feng, J., Chen, Y., Liu, W., Lin, Z., Yan, S.: Tensor robust principal component analysis with a new tensor nuclear norm. IEEE Trans. Pattern Anal. Mach. Intell. 42(4), 925\u2013938 (2020). https:\/\/doi.org\/10.1109\/TPAMI.2019.2891760","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"1785_CR8","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/1970392.1970395","volume":"58","author":"EJ Cand\u00e8s","year":"2011","unstructured":"Cand\u00e8s, E.J., Li, X., Ma, Y., Wright, J.: Robust principal component analysis? J. ACM (JACM) 58(3), 1\u201337 (2011)","journal-title":"J. ACM (JACM)"},{"key":"1785_CR9","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108590","volume":"244","author":"ZY Chen","year":"2022","unstructured":"Chen, Z.Y., Zhao, X.L., Lin, J., Chen, Y.: Nonlocal-based tensor-average-rank minimization and tensor transform-sparsity for 3d image denoising. Knowl.-Based Syst. 244, 108590 (2022). https:\/\/doi.org\/10.1016\/j.knosys.2022.108590. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0950705122002647)","journal-title":"Knowl.-Based Syst."},{"key":"1785_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2025.104406","volume":"107","author":"B Li","year":"2025","unstructured":"Li, B., Fan, Y., Zhang, W., Song, Y.: A two-step enhanced tensor denoising framework based on noise position prior and adaptive ring rank. J. Vis. Commun. Image Represent. 107, 104406 (2025). https:\/\/doi.org\/10.1016\/j.jvcir.2025.104406. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1047320325000203)","journal-title":"J. Vis. Commun. Image Represent."},{"issue":"1\u20134","key":"1785_CR11","doi-asserted-by":"publisher","first-page":"164","DOI":"10.1002\/sapm192761164","volume":"6","author":"FL Hitchcock","year":"1927","unstructured":"Hitchcock, F.L.: The expression of a tensor or a polyadic as a sum of products. J. Math. Phys. 6(1\u20134), 164\u2013189 (1927)","journal-title":"J. Math. Phys."},{"key":"1785_CR12","doi-asserted-by":"publisher","first-page":"12","DOI":"10.1016\/j.image.2018.03.017","volume":"73","author":"M Zhou","year":"2019","unstructured":"Zhou, M., Liu, Y., Long, Z., Chen, L., Zhu, C.: Tensor rank learning in CP decomposition via convolutional neural network. Signal Process. Image Commun. 73, 12\u201321 (2019). https:\/\/doi.org\/10.1016\/j.image.2018.03.017. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0923596518302741. Tensor Image Processing)","journal-title":"Signal Process. Image Commun."},{"issue":"3","key":"1785_CR13","doi-asserted-by":"publisher","first-page":"279","DOI":"10.1007\/BF02289464","volume":"31","author":"LR Tucker","year":"1966","unstructured":"Tucker, L.R.: Some mathematical notes on three-mode factor analysis. Psychometrika 31(3), 279\u2013311 (1966)","journal-title":"Psychometrika"},{"issue":"1","key":"1785_CR14","doi-asserted-by":"publisher","first-page":"208","DOI":"10.1109\/TPAMI.2012.39","volume":"35","author":"J Liu","year":"2012","unstructured":"Liu, J., Musialski, P., Wonka, P., Ye, J.: Tensor completion for estimating missing values in visual data. IEEE Trans. Pattern Anal. Mach. Intell. 35(1), 208\u2013220 (2012)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1785_CR15","unstructured":"Romera-Paredes, B., Pontil, M.: A new convex relaxation for tensor completion. Adv. Neural Inf. Process. Syst. 26 (2013)"},{"issue":"3","key":"1785_CR16","doi-asserted-by":"publisher","first-page":"641","DOI":"10.1016\/j.laa.2010.09.020","volume":"435","author":"ME Kilmer","year":"2011","unstructured":"Kilmer, M.E., Martin, C.D.: Factorization strategies for third-order tensors. Linear Algebra Appl. 435(3), 641\u2013658 (2011)","journal-title":"Linear Algebra Appl."},{"issue":"1","key":"1785_CR17","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1137\/110837711","volume":"34","author":"ME Kilmer","year":"2013","unstructured":"Kilmer, M.E., Braman, K., Hao, N., Hoover, R.C.: Third-order tensors as operators on matrices: a theoretical and computational framework with applications in imaging. SIAM J. Matrix Anal. Appl. 34(1), 148\u2013172 (2013)","journal-title":"SIAM J. Matrix Anal. Appl."},{"key":"1785_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2023.109545","volume":"140","author":"W Kong","year":"2023","unstructured":"Kong, W., Zhang, F., Qin, W., Wang, J.: Low-tubal-rank tensor recovery with multilayer subspace prior learning. Pattern Recogn. 140, 109545 (2023). https:\/\/doi.org\/10.1016\/j.patcog.2023.109545. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0031320323002455)","journal-title":"Pattern Recogn."},{"key":"1785_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2019.112680","volume":"372","author":"TX Jiang","year":"2020","unstructured":"Jiang, T.X., Huang, T.Z., Zhao, X.L., Deng, L.J.: Multi-dimensional imaging data recovery via minimizing the partial sum of tubal nuclear norm. J. Comput. Appl. Math. 372, 112680 (2020)","journal-title":"J. Comput. Appl. Math."},{"issue":"6","key":"1785_CR20","doi-asserted-by":"publisher","first-page":"2133","DOI":"10.1109\/TPAMI.2020.3017672","volume":"43","author":"Q Gao","year":"2020","unstructured":"Gao, Q., Zhang, P., Xia, W., Xie, D., Gao, X., Tao, D.: Enhanced tensor RPCA and its application. IEEE Trans. Pattern Anal. Mach. Intell. 43(6), 2133\u20132140 (2020)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"1","key":"1785_CR21","doi-asserted-by":"publisher","first-page":"1142","DOI":"10.1109\/TNNLS.2022.3182541","volume":"35","author":"X Zhang","year":"2022","unstructured":"Zhang, X., Zheng, J., Zhao, L., Zhou, Z., Lin, Z.: Tensor recovery with weighted tensor average rank. IEEE Trans. Neural Netw. Learn. Syst. 35(1), 1142\u20131156 (2022)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"1785_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.124809","volume":"255","author":"W Zhang","year":"2024","unstructured":"Zhang, W., Fan, Y., Song, Y., Tang, K., Li, B.: A generalized two-stage tensor denoising method based on the prior of the noise location and rank. Expert Syst. Appl. 255, 124809 (2024)","journal-title":"Expert Syst. Appl."},{"key":"1785_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.112921","volume":"310","author":"M Chen","year":"2025","unstructured":"Chen, M., Guo, K., Xu, X.: Tensor self-representation network for subspace clustering via alternating direction method of multipliers. Knowl.-Based Syst. 310, 112921 (2025). https:\/\/doi.org\/10.1016\/j.knosys.2024.112921. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0950705124015557)","journal-title":"Knowl.-Based Syst."},{"key":"1785_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.108468","volume":"243","author":"S Du","year":"2022","unstructured":"Du, S., Liu, B., Shan, G., Shi, Y., Wang, W.: Enhanced tensor low-rank representation for clustering and denoising. Knowl.-Based Syst. 243, 108468 (2022)","journal-title":"Knowl.-Based Syst."},{"issue":"5","key":"1785_CR25","doi-asserted-by":"publisher","first-page":"1718","DOI":"10.1109\/TPAMI.2019.2954874","volume":"43","author":"P Zhou","year":"2019","unstructured":"Zhou, P., Lu, C., Feng, J., Lin, Z., Yan, S.: Tensor low-rank representation for data recovery and clustering. IEEE Trans. Pattern Anal. Mach. Intell. 43(5), 1718\u20131732 (2019)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"1785_CR26","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1137\/07070111X","volume":"51","author":"TG Kolda","year":"2009","unstructured":"Kolda, T.G., Bader, B.W.: Tensor decompositions and applications. SIAM Rev. 51(3), 455\u2013500 (2009)","journal-title":"SIAM Rev."},{"key":"1785_CR27","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Ely, G., Aeron, S., Hao, N., Kilmer, M.: Novel methods for multilinear data completion and de-noising based on tensor-SVD. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 3842\u20133849 (2014)","DOI":"10.1109\/CVPR.2014.485"},{"key":"1785_CR28","doi-asserted-by":"crossref","unstructured":"Oh, T.H., Kim, H., Tai, Y.W., Bazin, J.C., So\u00a0Kweon, I.: Partial sum minimization of singular values in RPCA for low-level vision. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 145\u2013152 (2013)","DOI":"10.1109\/ICCV.2013.25"},{"issue":"4","key":"1785_CR29","doi-asserted-by":"publisher","first-page":"744","DOI":"10.1109\/TPAMI.2015.2465956","volume":"38","author":"TH Oh","year":"2015","unstructured":"Oh, T.H., Tai, Y.W., Bazin, J.C., Kim, H., Kweon, I.S.: Partial sum minimization of singular values in robust PCA: algorithm and applications. IEEE Trans. Pattern Anal. Mach. Intell. 38(4), 744\u2013758 (2015)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1785_CR30","doi-asserted-by":"publisher","first-page":"351","DOI":"10.1016\/j.neucom.2021.02.002","volume":"440","author":"S Du","year":"2021","unstructured":"Du, S., Shi, Y., Shan, G., Wang, W., Ma, Y.: Tensor low-rank sparse representation for tensor subspace learning. Neurocomputing 440, 351\u2013364 (2021). https:\/\/doi.org\/10.1016\/j.neucom.2021.02.002. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0925231221002125)","journal-title":"Neurocomputing"},{"key":"1785_CR31","doi-asserted-by":"publisher","first-page":"150350","DOI":"10.1109\/ACCESS.2020.3016777","volume":"8","author":"M Liu","year":"2020","unstructured":"Liu, M., Zhang, X., Tang, L.: Weighted t-Schatten-p norm minimization for real color image denoising. IEEE Access 8, 150350\u2013150359 (2020)","journal-title":"IEEE Access"},{"key":"1785_CR32","doi-asserted-by":"crossref","unstructured":"Yan, Y., Zhang, X., Zheng, J., Zhao, L.: Weighted tensor schatten p-norm minimization for image denoising. In: Proceedings of 2018 Chinese Intelligent Systems Conference: Volume I, pp. 163\u2013172, Springer (2019)","DOI":"10.1007\/978-981-13-2288-4_17"},{"issue":"476","key":"1785_CR33","doi-asserted-by":"publisher","first-page":"1418","DOI":"10.1198\/016214506000000735","volume":"101","author":"H Zou","year":"2006","unstructured":"Zou, H.: The adaptive lasso and its oracle properties. J. Am. Stat. Assoc. 101(476), 1418\u20131429 (2006)","journal-title":"J. Am. Stat. Assoc."},{"issue":"3","key":"1785_CR34","doi-asserted-by":"publisher","first-page":"681","DOI":"10.1109\/TIP.2010.2076294","volume":"20","author":"MV Afonso","year":"2011","unstructured":"Afonso, M.V., Bioucas-Dias, J.M., Figueiredo, M.A.T.: An augmented Lagrangian approach to the constrained optimization formulation of imaging inverse problems. IEEE Trans. Image Process. 20(3), 681\u2013695 (2011). https:\/\/doi.org\/10.1109\/TIP.2010.2076294","journal-title":"IEEE Trans. Image Process."},{"issue":"10","key":"1785_CR35","doi-asserted-by":"publisher","first-page":"4842","DOI":"10.1109\/TIP.2016.2599290","volume":"25","author":"Y Xie","year":"2016","unstructured":"Xie, Y., Gu, S., Liu, Y., Zuo, W., Zhang, W., Zhang, L.: Weighted Schatten $$p$$ -norm minimization for image denoising and background subtraction. IEEE Trans. Image Process. 25(10), 4842\u20134857 (2016). https:\/\/doi.org\/10.1109\/TIP.2016.2599290","journal-title":"IEEE Trans. Image Process."},{"key":"1785_CR36","doi-asserted-by":"publisher","first-page":"3132","DOI":"10.1109\/TIP.2019.2957925","volume":"29","author":"H Zhang","year":"2020","unstructured":"Zhang, H., Qian, J., Zhang, B., Yang, J., Gong, C., Wei, Y.: Low-rank matrix recovery via modified Schatten-p norm minimization with convergence guarantees. IEEE Trans. Image Process. 29, 3132\u20133142 (2020). https:\/\/doi.org\/10.1109\/TIP.2019.2957925","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"1785_CR37","doi-asserted-by":"publisher","first-page":"2765","DOI":"10.1109\/TPAMI.2013.57","volume":"35","author":"E Elhamifar","year":"2013","unstructured":"Elhamifar, E., Vidal, R.: Sparse subspace clustering: algorithm, theory, and applications. IEEE Trans. Pattern Anal. Mach. Intell. 35(11), 2765\u20132781 (2013). https:\/\/doi.org\/10.1109\/TPAMI.2013.57","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1785_CR38","first-page":"2837","volume":"11","author":"NX Vinh","year":"2010","unstructured":"Vinh, N.X., Epps, J., Bailey, J.: Information theoretic measures for clusterings comparison: Variants, properties, normalization and correction for chance. J. Mach. Learn. Res. 11, 2837\u20132854 (2010)","journal-title":"J. Mach. Learn. Res."},{"key":"1785_CR39","volume-title":"Introduction to Information Retrieval","author":"H Sch\u00fctze","year":"2008","unstructured":"Sch\u00fctze, H., Manning, C.D., Raghavan, P.: Introduction to Information Retrieval, vol. 39. Cambridge University Press, Cambridge (2008)"},{"key":"1785_CR40","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.ins.2022.07.049","volume":"609","author":"B Cai","year":"2022","unstructured":"Cai, B., Lu, G.F.: Tensor subspace clustering using consensus tensor low-rank representation. Inf. Sci. 609, 46\u201359 (2022). https:\/\/doi.org\/10.1016\/j.ins.2022.07.049. (https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0020025522007381)","journal-title":"Inf. Sci."},{"issue":"2","key":"1785_CR41","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1109\/TPAMI.2008.79","volume":"31","author":"J Wright","year":"2009","unstructured":"Wright, J., Yang, A.Y., Ganesh, A., Sastry, S.S., Ma, Y.: Robust face recognition via sparse representation. IEEE Trans. Pattern Anal. Mach. Intell. 31(2), 210\u2013227 (2009). https:\/\/doi.org\/10.1109\/TPAMI.2008.79","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"5","key":"1785_CR42","doi-asserted-by":"publisher","first-page":"1080","DOI":"10.1109\/TNNLS.2015.2436951","volume":"27","author":"P Zhou","year":"2016","unstructured":"Zhou, P., Lin, Z., Zhang, C.: Integrated low-rank-based discriminative feature learning for recognition. IEEE Trans. Neural Netw. Learn. Syst. 27(5), 1080\u20131093 (2016). https:\/\/doi.org\/10.1109\/TNNLS.2015.2436951","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"issue":"8","key":"1785_CR43","doi-asserted-by":"publisher","first-page":"888","DOI":"10.1109\/34.868688","volume":"22","author":"J Shi","year":"2000","unstructured":"Shi, J., Malik, J.: Normalized cuts and image segmentation. IEEE Trans. Pattern Anal. Mach. Intell. 22(8), 888\u2013905 (2000). https:\/\/doi.org\/10.1109\/34.868688","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1785_CR44","doi-asserted-by":"publisher","first-page":"347","DOI":"10.1007\/978-3-642-33786-4_26","volume-title":"Computer Vision - ECCV 2012","author":"CY Lu","year":"2012","unstructured":"Lu, C.Y., Min, H., Zhao, Z.Q., Zhu, L., Huang, D.S., Yan, S.: Robust and Efficient Subspace Segmentation via Least Squares Regression. In: Fitzgibbon, A., Lazebnik, S., Perona, P., Sato, Y., Schmid, C. (eds.) Computer Vision - ECCV 2012, pp. 347\u2013360. Springer, Berlin Heidelberg (2012)"},{"issue":"1","key":"1785_CR45","doi-asserted-by":"publisher","first-page":"171","DOI":"10.1109\/TPAMI.2012.88","volume":"35","author":"G Liu","year":"2013","unstructured":"Liu, G., Lin, Z., Yan, S., Sun, J., Yu, Y., Ma, Y.: Robust recovery of subspace structures by low-rank representation. IEEE Trans. Pattern Anal. Mach. Intell. 35(1), 171\u2013184 (2013). https:\/\/doi.org\/10.1109\/TPAMI.2012.88","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"1785_CR46","unstructured":"Wu, T.: Robust data clustering with outliers via transformed tensor low-rank representation. In: International Conference on Artificial Intelligence and Statistics (PMLR, 2024), pp. 1756\u20131764"},{"key":"1785_CR47","doi-asserted-by":"publisher","unstructured":"Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In: Proceedings Eighth IEEE International Conference on Computer Vision. ICCV 2001, vol.\u00a02, pp. 416\u2013423 (2001) https:\/\/doi.org\/10.1109\/ICCV.2001.937655","DOI":"10.1109\/ICCV.2001.937655"},{"issue":"8","key":"1785_CR48","doi-asserted-by":"publisher","first-page":"2378","DOI":"10.1109\/TIP.2011.2109730","volume":"20","author":"L Zhang","year":"2011","unstructured":"Zhang, L., Zhang, L., Mou, X., Zhang, D.: FSIM: a feature similarity index for image quality assessment. IEEE Trans. Image Process. 20(8), 2378\u20132386 (2011). https:\/\/doi.org\/10.1109\/TIP.2011.2109730","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"1785_CR49","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1109\/TPAMI.2016.2539946","volume":"39","author":"G Liu","year":"2017","unstructured":"Liu, G., Liu, Q., Li, P.: Blessing of dimensionality: recovering mixture data via dictionary pursuit. IEEE Trans. Pattern Anal. Mach. Intell. 39(1), 47\u201360 (2017). https:\/\/doi.org\/10.1109\/TPAMI.2016.2539946","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Machine Vision and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00138-025-01785-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00138-025-01785-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00138-025-01785-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,9]],"date-time":"2026-03-09T18:13:12Z","timestamp":1773079992000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00138-025-01785-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,21]]},"references-count":49,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["1785"],"URL":"https:\/\/doi.org\/10.1007\/s00138-025-01785-7","relation":{},"ISSN":["0932-8092","1432-1769"],"issn-type":[{"value":"0932-8092","type":"print"},{"value":"1432-1769","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,21]]},"assertion":[{"value":"7 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 December 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 December 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 January 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"25"}}