{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T19:47:50Z","timestamp":1776800870331,"version":"3.51.2"},"reference-count":63,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,1,4]],"date-time":"2025-01-04T00:00:00Z","timestamp":1735948800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,4]],"date-time":"2025-01-04T00:00:00Z","timestamp":1735948800000},"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":["12071380"],"award-info":[{"award-number":["12071380"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["12201505"],"award-info":[{"award-number":["12201505"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Natural Key Research and Development Program of China","award":["2021YFB3101500"],"award-info":[{"award-number":["2021YFB3101500"]}]},{"name":"Sichuan Science and Technology Program","award":["2023NSFSC0060"],"award-info":[{"award-number":["2023NSFSC0060"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Appl Intell"],"published-print":{"date-parts":[[2025,2]]},"DOI":"10.1007\/s10489-024-06024-6","type":"journal-article","created":{"date-parts":[[2025,1,4]],"date-time":"2025-01-04T09:13:45Z","timestamp":1735982025000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Image denoising via double-weighted correlated total variation regularization"],"prefix":"10.1007","volume":"55","author":[{"given":"Zhihao","family":"Zhang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Peng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinling","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jingyao","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingrong","family":"Feng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5344-4460","authenticated-orcid":false,"given":"Jianjun","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,1,4]]},"reference":[{"key":"6024_CR1","doi-asserted-by":"crossref","DOI":"10.1016\/j.compbiomed.2022.106474","volume":"152","author":"E Goceri","year":"2023","unstructured":"Goceri E (2023) Evaluation of denoising techniques to remove speckle and gaussian noise from dermoscopy images. Comput Biol Med 152:106474","journal-title":"Comput Biol Med"},{"issue":"1","key":"6024_CR2","first-page":"240","volume":"30","author":"A Suneetha","year":"2020","unstructured":"Suneetha A, Srinivasa Reddy E (2020) Robust gaussian noise detection and removal in color images using modified fuzzy set filter. J Intell Syst 30(1):240\u2013257","journal-title":"J Intell Syst"},{"issue":"3","key":"6024_CR3","first-page":"505","volume":"34","author":"A Shah","year":"2022","unstructured":"Shah A, Bangash JI, Khan AW, Ahmed I, Khan A, Khan A, Khan A (2022) Comparative analysis of median filter and its variants for removal of impulse noise from gray scale images. J King Saud Univ-Comput Inf Sci 34(3):505\u2013519","journal-title":"J King Saud Univ-Comput Inf Sci"},{"issue":"4","key":"6024_CR4","doi-asserted-by":"crossref","first-page":"1227","DOI":"10.1109\/JSTARS.2017.2779539","volume":"11","author":"Y Wang","year":"2017","unstructured":"Wang Y, Peng J, Zhao Q, Leung Y, Zhao XL, Meng D (2017) Hyperspectral image restoration via total variation regularized low-rank tensor decomposition. IEEE J Sel Top Appl Earth Obs Remote Sens 11(4):1227\u20131243","journal-title":"IEEE J Sel Top Appl Earth Obs Remote Sens"},{"issue":"5","key":"6024_CR5","first-page":"5519","volume":"53","author":"E Zhou","year":"2023","unstructured":"Zhou E, Xu X, Xu B, Wu H (2023) An enhancement model based on dense atrous and inception convolution for image semantic segmentation. Applied Intelligence 53(5):5519\u20135531","journal-title":"Applied Intelligence"},{"key":"6024_CR6","doi-asserted-by":"crossref","first-page":"8427","DOI":"10.1007\/s12652-020-02572-0","volume":"12","author":"J Zhang","year":"2021","unstructured":"Zhang J, Sun J, Wang J, Yue XG (2021) Visual object tracking based on residual network and cascaded correlation filters. Journal of ambient intelligence and humanized computing 12:8427\u20138440","journal-title":"Journal of ambient intelligence and humanized computing"},{"key":"6024_CR7","doi-asserted-by":"crossref","unstructured":"Padilla R, Netto SL, Da\u00a0Silva EA (2020) A survey on performance metrics for object-detection algorithms. In: Proc. Int. Conf. Syst., Signals Image Process. (IWSSIP), pp 237\u2013242","DOI":"10.1109\/IWSSIP48289.2020.9145130"},{"key":"6024_CR8","doi-asserted-by":"crossref","first-page":"1687","DOI":"10.1007\/s10489-019-01612-3","volume":"50","author":"S Zheng","year":"2020","unstructured":"Zheng S, Zhang Y, Liu W, Zou Y (2020) Improved image representation and sparse representation for image classification. Applied Intelligence 50:1687\u20131698","journal-title":"Applied Intelligence"},{"issue":"3","key":"6024_CR9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1970392.1970395","volume":"58","author":"EJ Cand\u00e8s","year":"2011","unstructured":"Cand\u00e8s EJ, Li X, Ma Y, Wright J (2011) Robust principal component analysis? J. ACM 58(3):1\u201337","journal-title":"J. ACM"},{"issue":"4","key":"6024_CR10","doi-asserted-by":"crossref","first-page":"1777","DOI":"10.1109\/TIP.2017.2781425","volume":"27","author":"H Wang","year":"2007","unstructured":"Wang H, Cen Y, He Z, He Z, Zhao R, Zhang F (2007) Reweighted low-rank matrix analysis with structural smoothness for image denoising. IEEE Trans Image Process 27(4):1777\u20131792","journal-title":"IEEE Trans Image Process"},{"key":"6024_CR11","doi-asserted-by":"crossref","unstructured":"Peng J, Wang Y, Zhang H, Wang J, Meng D (2022) Exact decomposition of joint low rankness and local smoothness plus sparse matrices. IEEE Trans Pattern Anal Mach Intell","DOI":"10.1109\/TPAMI.2022.3204203"},{"key":"6024_CR12","doi-asserted-by":"crossref","first-page":"2244","DOI":"10.1109\/TIP.2019.2949383","volume":"29","author":"Y Huang","year":"2019","unstructured":"Huang Y, Liao G, Xiang Y, Zhang L, Li J, Nehorai A (2019) Low-rank approximation via generalized reweighted iterative nuclear and frobenius norms. IEEE Trans Image Process 29:2244\u20132257","journal-title":"IEEE Trans Image Process"},{"key":"6024_CR13","doi-asserted-by":"crossref","unstructured":"Gu S, Zhang L, Zuo W, Feng X (2014) Weighted nuclear norm minimization with application to image denoising. In: Proc IEEE Conf Comput Vis Pattern Recognit (CVPR), pp 2862\u20132869","DOI":"10.1109\/CVPR.2014.366"},{"key":"6024_CR14","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1007\/s11263-016-0930-5","volume":"121","author":"S Gu","year":"2017","unstructured":"Gu S, Xie Q, Meng D, Zuo W, Feng X, Zhang L (2017) Weighted nuclear norm minimization and its applications to low level vision. Int J Comput Vision 121:183\u2013208","journal-title":"Int J Comput Vision"},{"issue":"10","key":"6024_CR15","doi-asserted-by":"crossref","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 (2016) Weighted schatten $$ p $$-norm minimization for image denoising and background subtraction. IEEE Trans Image Process 25(10):4842\u20134857","journal-title":"IEEE Trans Image Process"},{"key":"6024_CR16","doi-asserted-by":"crossref","first-page":"3514","DOI":"10.1109\/TSP.2022.3183466","volume":"70","author":"L Chen","year":"2022","unstructured":"Chen L, Jiang X, Liu X, Haardt M (2022) Reweighted low-rank factorization with deep prior for image restoration. IEEE Trans Signal Process 70:3514\u20133529","journal-title":"IEEE Trans Signal Process"},{"key":"6024_CR17","doi-asserted-by":"crossref","first-page":"877","DOI":"10.1007\/s00041-008-9045-x","volume":"14","author":"EJ Candes","year":"2008","unstructured":"Candes EJ, Wakin MB, Boyd SP (2008) Enhancing sparsity by reweighted $$l_1$$ minimization. J Fourier Anal Appl 14:877\u2013905","journal-title":"J Fourier Anal Appl"},{"issue":"10","key":"6024_CR18","doi-asserted-by":"crossref","first-page":"4677","DOI":"10.1109\/TIP.2016.2593343","volume":"25","author":"X Cao","year":"2016","unstructured":"Cao X, Zhao Q, Meng D, Chen Y, Xu Z (2016) Robust low-rank matrix factorization under general mixture noise distributions. IEEE Trans Image Process 25(10):4677\u20134690","journal-title":"IEEE Trans Image Process"},{"key":"6024_CR19","doi-asserted-by":"crossref","unstructured":"Cao X, Chen Y, Zhao Q, Meng D, Wang Y, Wang D, Xu Z (2015) Low-rank matrix factorization under general mixture noise distributions. In: Proc. IEEE Int Conf Comput Vis (ICCV), pp 1493\u20131501","DOI":"10.1109\/ICCV.2015.175"},{"issue":"3","key":"6024_CR20","doi-asserted-by":"crossref","first-page":"1054","DOI":"10.1109\/TCYB.2017.2677944","volume":"48","author":"Y Chen","year":"2017","unstructured":"Chen Y, Cao X, Zhao Q, Meng D, Xu Z (2017) Denoising hyperspectral image with non-iid noise structure. IEEE Trans Cybern 48(3):1054\u20131066","journal-title":"IEEE Trans Cybern"},{"issue":"1","key":"6024_CR21","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1109\/TGRS.2019.2940534","volume":"58","author":"YB Zheng","year":"2019","unstructured":"Zheng YB, Huang TZ, Zhao XL, Jiang TX, Ma TH, Ji TY (2019) Mixed noise removal in hyperspectral image via low-fibered-rank regularization. IEEE Trans Geosci Remote Sens 58(1):734\u2013749","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"6","key":"6024_CR22","doi-asserted-by":"crossref","first-page":"2991","DOI":"10.1109\/TIP.2019.2893068","volume":"28","author":"J Yao","year":"2019","unstructured":"Yao J, Meng D, Zhao Q, Cao W, Xu Z (2019) Nonconvex-sparsity and nonlocal-smoothness-based blind hyperspectral unmixing. IEEE Trans Image Process 28(6):2991\u20133006","journal-title":"IEEE Trans Image Process"},{"issue":"8","key":"6024_CR23","doi-asserted-by":"crossref","first-page":"1888","DOI":"10.1109\/TPAMI.2017.2734888","volume":"40","author":"Q Xie","year":"2017","unstructured":"Xie Q, Zhao Q, Meng D, Xu Z (2017) Kronecker-basis-representation based tensor sparsity and its applications to tensor recovery. IEEE Trans Pattern Anal Mach Intell 40(8):1888\u20131902","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"key":"6024_CR24","doi-asserted-by":"crossref","unstructured":"He W, Yao Q, Li C, Yokoya N, Zhao Q (2019) Non-local meets global: An integrated paradigm for hyperspectral denoising. In: Proc IEEE Conf Comput Vis Pattern Recognit (CVPR), pp 6868\u20136877","DOI":"10.1109\/CVPR.2019.00703"},{"key":"6024_CR25","doi-asserted-by":"crossref","first-page":"7889","DOI":"10.1109\/TIP.2020.3007840","volume":"29","author":"J Peng","year":"2020","unstructured":"Peng J, Xie Q, Zhao Q, Wang Y, Yee L, Meng D (2020) Enhanced 3dtv regularization and its applications on hsi denoising and compressed sensing. IEEE Trans Image Process 29:7889\u20137903","journal-title":"IEEE Trans Image Process"},{"key":"6024_CR26","first-page":"1","volume":"60","author":"J Peng","year":"2022","unstructured":"Peng J, Wang H, Cao X, Liu X, Rui X, Meng D (2022) Fast noise removal in hyperspectral images via representative coefficient total variation. IEEE Trans Geosci Remote Sens 60:1\u201317","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"9","key":"6024_CR27","doi-asserted-by":"crossref","first-page":"10990","DOI":"10.1109\/TPAMI.2023.3259640","volume":"45","author":"H Wang","year":"2023","unstructured":"Wang H, Peng J, Qin W, Wang J, Meng D (2023) Guaranteed tensor recovery fused low-rankness and smoothness. IEEE Trans Patt Anal Mach Intell 45(9):10990\u201311007","journal-title":"IEEE Trans Patt Anal Mach Intell"},{"issue":"3","key":"6024_CR28","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/s10915-024-02509-1","volume":"99","author":"K Huang","year":"2024","unstructured":"Huang K, Kong W, Zhou M, Qin W, Zhang F, Wang J (2024) Enhanced low-rank tensor recovery fusing reweighted tensor correlated total variation regularization for image denoising. J Sci Comput 99(3):69","journal-title":"J Sci Comput"},{"issue":"9","key":"6024_CR29","doi-asserted-by":"crossref","first-page":"2117","DOI":"10.1109\/TPAMI.2012.271","volume":"35","author":"Y Hu","year":"2012","unstructured":"Hu Y, Zhang D, Ye J, Li X, He X (2012) Fast and accurate matrix completion via truncated nuclear norm regularization. IEEE Trans Pattern Anal Mach Intell 35(9):2117\u20132130","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"6024_CR30","first-page":"013044","volume":"28","author":"G Chen","year":"2019","unstructured":"Chen G, Wang J, Zhang F, Wang W (2019) Image denoising in impulsive noise via weighted schatten p-norm regularization. J Electron Imaging 28(1):013044\u2013013044","journal-title":"J Electron Imaging"},{"issue":"12","key":"6024_CR31","doi-asserted-by":"crossref","first-page":"2418","DOI":"10.1109\/TCYB.2014.2307854","volume":"44","author":"Y Peng","year":"2014","unstructured":"Peng Y, Suo J, Dai Q, Xu W (2014) Reweighted low-rank matrix recovery and its application in image restoration. IEEE Trans Cybern 44(12):2418\u20132430","journal-title":"IEEE Trans Cybern"},{"key":"6024_CR32","doi-asserted-by":"crossref","unstructured":"Xu Z, Xing H, Fang S, Wu S, Xie S (2021) Double-weighted low-rank matrix recovery based on rank estimation. In: Proc. IEEE Int Conf Comput Vis (ICCV), pp 172\u2013180","DOI":"10.1109\/ICCVW54120.2021.00024"},{"issue":"8","key":"6024_CR33","doi-asserted-by":"crossref","first-page":"4729","DOI":"10.1109\/TGRS.2013.2284280","volume":"52","author":"H Zhang","year":"2013","unstructured":"Zhang H, He W, Zhang L, Shen H, Yuan Q (2013) Hyperspectral image restoration using low-rank matrix recovery. IEEE Trans Geosci Remote Sens 52(8):4729\u20134743","journal-title":"IEEE Trans Geosci Remote Sens"},{"issue":"4","key":"6024_CR34","doi-asserted-by":"crossref","first-page":"925","DOI":"10.1109\/TPAMI.2019.2891760","volume":"42","author":"C Lu","year":"2019","unstructured":"Lu C, Feng J, Chen Y, Liu W, Lin Z, Yan S (2019) Tensor robust principal component analysis with a new tensor nuclear norm. IEEE Trans Pattern Anal Mach Intell 42(4):925\u2013938","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"1","key":"6024_CR35","doi-asserted-by":"crossref","first-page":"383","DOI":"10.1109\/TIT.2022.3198725","volume":"69","author":"J Wang","year":"2022","unstructured":"Wang J, Hou J, Eldar YC (2022) Tensor robust principal component analysis from multilevel quantized observations. IEEE Trans Inf Theory 69(1):383\u2013406","journal-title":"IEEE Trans Inf Theory"},{"key":"6024_CR36","doi-asserted-by":"crossref","unstructured":"Zhang F, Wang H, Qin W, Zhao X, Wang J (2023) Generalized nonconvex regularization for tensor rpca and its applications in visual inpainting. Appl Intell, 1\u201323","DOI":"10.1007\/s10489-023-04744-9"},{"issue":"3","key":"6024_CR37","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1137\/07070111X","volume":"51","author":"TG Kolda","year":"2009","unstructured":"Kolda TG, Bader BW (2009) Tensor decompositions and applications. SIAM Rev 51(3):455\u2013500","journal-title":"SIAM Rev"},{"issue":"13","key":"6024_CR38","doi-asserted-by":"crossref","first-page":"3551","DOI":"10.1109\/TSP.2017.2690524","volume":"65","author":"ND Sidiropoulos","year":"2017","unstructured":"Sidiropoulos ND, De Lathauwer L, Fu X, Huang K, Papalexakis EE, Faloutsos C (2017) Tensor decomposition for signal processing and machine learning. IEEE Trans Signal Process 65(13):3551\u20133582","journal-title":"IEEE Trans Signal Process"},{"issue":"5","key":"6024_CR39","first-page":"2295","volume":"33","author":"IV Oseledets","year":"2011","unstructured":"Oseledets IV (2011) Tensor-train decomposition. SIAM. J Sci Comput 33(5):2295\u20132317","journal-title":"J Sci Comput"},{"key":"6024_CR40","first-page":"60","volume":"2","author":"A Buades","year":"2005","unstructured":"Buades A, Coll B, Morel JM (2005) A non-local algorithm for image denoising. Proc IEEE Conf Comput Vis Pattern Recognit (CVPR) 2:60\u201365","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit (CVPR)"},{"issue":"8","key":"6024_CR41","doi-asserted-by":"crossref","first-page":"2080","DOI":"10.1109\/TIP.2007.901238","volume":"16","author":"K Dabov","year":"2007","unstructured":"Dabov K, Foi A, Katkovnik V, Egiazarian K (2007) Image denoising by sparse 3-d transform-domain collaborative filtering. IEEE Trans Image Process 16(8):2080\u20132095","journal-title":"IEEE Trans Image Process"},{"issue":"1","key":"6024_CR42","doi-asserted-by":"crossref","first-page":"119","DOI":"10.1109\/TIP.2012.2210725","volume":"22","author":"M Maggioni","year":"2012","unstructured":"Maggioni M, Katkovnik V, Egiazarian K, Foi A (2012) Nonlocal transform-domain filter for volumetric data denoising and reconstruction. IEEE Trans Image Process 22(1):119\u2013133","journal-title":"IEEE Trans Image Process"},{"key":"6024_CR43","doi-asserted-by":"crossref","unstructured":"Xu J, Zhang L, Zhang D, Feng X (2017) Hyper-laplacian regularized unidirectional low-rank tensor recovery for multispectral image denoising. In: Proc. IEEE Int Conf Comput Vis (ICCV), pp 1096\u20131104","DOI":"10.1109\/CVPR.2017.625"},{"key":"6024_CR44","doi-asserted-by":"crossref","unstructured":"Huang X, Du B, Liu W (2021) Multichannel color image denoising via weighted schatten p-norm minimization. In: Proc 29th Int Joint Conf Artif Intell, pp 637\u2013644","DOI":"10.24963\/ijcai.2020\/89"},{"key":"6024_CR45","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.ins.2020.05.049","volume":"537","author":"Y Su","year":"2020","unstructured":"Su Y, Li Z, Yu H, Wang Z (2020) Multi-band weighted $$l_p$$ norm minimization for image denoising. Inf Sci 537:162\u2013183","journal-title":"Inf Sci"},{"key":"6024_CR46","doi-asserted-by":"crossref","unstructured":"Yair N, Michaeli T (2018) Multi-scale weighted nuclear norm image restoration. In: Proc IEEE Conf Comput Vis Pattern Recognit (CVPR), pp 3165\u20133174","DOI":"10.1109\/CVPR.2018.00334"},{"key":"6024_CR47","doi-asserted-by":"crossref","unstructured":"Chang Y, Yan L, Zhong S (2017) Hyper-laplacian regularized unidirectional low-rank tensor recovery for multispectral image denoising. In: Proc IEEE Conf Comput Vis Pattern Recognit (CVPR), pp 4260\u20134268","DOI":"10.1109\/CVPR.2017.625"},{"key":"6024_CR48","doi-asserted-by":"crossref","unstructured":"Iordache MD, Bioucas-Dias JM, Plaza A (20112) Total variation spatial regularization for sparse hyperspectral unmixing. IEEE Trans Geosci Remote Sens 50(11):4484\u20134502","DOI":"10.1109\/TGRS.2012.2191590"},{"key":"6024_CR49","first-page":"1","volume":"60","author":"C Peng","year":"2022","unstructured":"Peng C, Liu Y, Kang K, Chen Y, Wu X, Cheng A, Kang Z, Chen C, Cheng Q (2022) Hyperspectral image denoising using nonconvex local low-rank and sparse separation with spatial-spectral total variation regularization. IEEE Trans Geosci Remote Sens 60:1\u201317","journal-title":"IEEE Trans Geosci Remote Sens"},{"key":"6024_CR50","doi-asserted-by":"crossref","unstructured":"Fan H, Li C, Guo Y, Kuang G, Ma J (2018) Spatial-spectral total variation regularized low-rank tensor decomposition for hyperspectral image denoising. IEEE Trans Geosci Remote Sens 56(10):6196\u20136213","DOI":"10.1109\/TGRS.2018.2833473"},{"key":"6024_CR51","doi-asserted-by":"crossref","unstructured":"Zeng H, Xie X, Cui H, Yin H, Ning J (2020) Hyperspectral image restoration via global $${l_{1 - 2}}$$ spatial-spectral total variation regularized local low-rank tensor recovery. IEEE Trans Geosci Remote Sens 59(4):3309\u20133325","DOI":"10.1109\/TGRS.2020.3007945"},{"key":"6024_CR52","unstructured":"Peng J, Zeng D, Ma J, Wang Y, Meng D (2018) Cpct-lrtdtv: cerebral perfusion ct image restoration via a low rank tensor decomposition with total variation regularization. In: Proc Med Imag Phys Med Imag, pp 821\u2013825. SPIE"},{"issue":"2","key":"6024_CR53","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1109\/TMI.2018.2865198","volume":"38","author":"S Li","year":"2018","unstructured":"Li S, Zeng D, Peng J, Bian Z, Zhang H, Xie Q, Wang Y, Liao Y, Zhang S, Huang J et al (2018) An efficient iterative cerebral perfusion ct reconstruction via low-rank tensor decomposition with spatial-temporal total variation regularization. IEEE Trans Med Imaging 38(2):360\u2013370","journal-title":"IEEE Trans Med Imaging"},{"key":"6024_CR54","unstructured":"Lin Z, Chen M, Ma Y (2010) The augmented lagrange multiplier method for exact recovery of corrupted low-rank matrices. arXiv preprint arXiv:1009.5055"},{"issue":"1","key":"6024_CR55","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1561\/2200000016","volume":"3","author":"S Boyd","year":"2011","unstructured":"Boyd S, Parikh N, Chu E, Peleato B, Eckstein J et al (2011) Distributed optimization and statistical learning via the alternating direction method of multipliers. Found Trends Mach Learn 3(1):1\u2013122","journal-title":"Found Trends Mach Learn"},{"key":"6024_CR56","unstructured":"Krishnan D, Fergus R (2009) Fast image deconvolution using hyper-laplacian priors. in Proc Adv Neural Inf Process 22"},{"issue":"3","key":"6024_CR57","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1109\/18.382009","volume":"41","author":"DL Donoho","year":"1995","unstructured":"Donoho DL (1995) De-noising by soft-thresholding. IEEE Trans Inf Theory 41(3):613\u2013627","journal-title":"IEEE Trans Inf Theory"},{"key":"6024_CR58","doi-asserted-by":"crossref","unstructured":"Zhou Z, Li X, Wright J, Candes E, Ma Y (2010) Stable principal component pursuit. In: Proc IEEE Int Symp Inf Theory, pp 1518\u20131522","DOI":"10.1109\/ISIT.2010.5513535"},{"key":"6024_CR59","doi-asserted-by":"crossref","first-page":"110","DOI":"10.1016\/j.rse.2007.07.028","volume":"113","author":"A Plaza","year":"2009","unstructured":"Plaza A, Benediktsson JA, Boardman JW, Brazile J, Bruzzone L, Camps-Valls G, Chanussot J, Fauvel M, Gamba P, Gualtieri A et al (2009) Recent advances in techniques for hyperspectral image processing. Remote Sens Environ 113:110\u2013122","journal-title":"Remote Sens Environ"},{"key":"6024_CR60","first-page":"3854635","volume":"1","author":"D Datta","year":"2022","unstructured":"Datta D, Mallick PK, Bhoi AK, Ijaz MF, Shafi J (2022) Choi J (2022) Hyperspectral image classification: Potentials, challenges, and future directions. Comput Intell Neurosci 1:3854635","journal-title":"Comput Intell Neurosci"},{"issue":"3","key":"6024_CR61","doi-asserted-by":"crossref","first-page":"1457","DOI":"10.1109\/TPAMI.2020.3015691","volume":"44","author":"Q Xie","year":"2020","unstructured":"Xie Q, Zhou M, Zhao Q, Xu Z, Meng D (2020) Mhf-net: An interpretable deep network for multispectral and hyperspectral image fusion. IEEE Trans Pattern Anal Mach Intell 44(3):1457\u20131473","journal-title":"IEEE Trans Pattern Anal Mach Intell"},{"issue":"9","key":"6024_CR62","doi-asserted-by":"crossref","first-page":"2241","DOI":"10.1109\/TIP.2010.2046811","volume":"19","author":"F Yasuma","year":"2010","unstructured":"Yasuma F, Mitsunaga T, Iso D, Nayar SK (2010) Generalized assorted pixel camera: postcapture control of resolution, dynamic range, and spectrum. IEEE Trans Image Process 19(9):2241\u20132253","journal-title":"IEEE Trans Image Process"},{"key":"6024_CR63","volume":"61","author":"SVM Sagheer","year":"2020","unstructured":"Sagheer SVM, George SN (2020) A review on medical image denoising algorithms. Biomed Signal Process Control 61:102036","journal-title":"Biomed Signal Process Control"}],"container-title":["Applied Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-06024-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10489-024-06024-6\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10489-024-06024-6.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,31]],"date-time":"2025-01-31T14:53:30Z","timestamp":1738335210000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10489-024-06024-6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1,4]]},"references-count":63,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,2]]}},"alternative-id":["6024"],"URL":"https:\/\/doi.org\/10.1007\/s10489-024-06024-6","relation":{},"ISSN":["0924-669X","1573-7497"],"issn-type":[{"value":"0924-669X","type":"print"},{"value":"1573-7497","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1,4]]},"assertion":[{"value":"17 September 2024","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 January 2025","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest\/Competing interests"}},{"value":"Not applicable.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"Not applicable.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent to participate"}},{"value":"Not applicable.","order":5,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}],"article-number":"269"}}