{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T11:39:39Z","timestamp":1774957179983,"version":"3.50.1"},"reference-count":36,"publisher":"Springer Science and Business Media LLC","issue":"5","license":[{"start":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T00:00:00Z","timestamp":1603843200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T00:00:00Z","timestamp":1603843200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation","doi-asserted-by":"crossref","award":["61501069"],"award-info":[{"award-number":["61501069"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Technology Innovation and Application Development Project of Chongqing","award":["cstc2019jscx-msxmX0167"],"award-info":[{"award-number":["cstc2019jscx-msxmX0167"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,2]]},"DOI":"10.1007\/s11042-020-09907-1","type":"journal-article","created":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T22:02:41Z","timestamp":1603922561000},"page":"7433-7450","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Recovery of image and video based on compressive sensing via tensor approximation and Spatio-temporal correlation"],"prefix":"10.1007","volume":"80","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5689-1146","authenticated-orcid":false,"given":"Yuanhong","family":"Zhong","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaokun","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyu","family":"Cheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guan","family":"Huang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qiang","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2020,10,28]]},"reference":[{"issue":"23","key":"9907_CR1","doi-asserted-by":"publisher","first-page":"5905","DOI":"10.1109\/TSP.2013.2279362","volume":"61","author":"MS Asif","year":"2013","unstructured":"Asif MS, Romberg J (2013) Fast and accurate algorithms for re-weighted \u21131-norm minimization. IEEE Trans Signal Process 61(23):5905\u20135916","journal-title":"IEEE Trans Signal Process"},{"key":"9907_CR2","doi-asserted-by":"publisher","unstructured":"Baraniuk RG, Cevher V, Duarte MF, et al (2010) Model-based compressive sensing. IEEE Trans Inf Theory 56(4)1982\u20132001. https:\/\/doi.org\/10.1109\/TIT.2010.2040894","DOI":"10.1109\/TIT.2010.2040894"},{"issue":"1","key":"9907_CR3","doi-asserted-by":"publisher","first-page":"34","DOI":"10.1137\/060657704","volume":"51","author":"AM Bruckstein","year":"2009","unstructured":"Bruckstein AM, Donoho DL, Elad M (2009) From sparse solutions of systems of equations to sparse modeling of signals and images. SIAM Rev 51(1):34\u201381","journal-title":"SIAM Rev"},{"key":"9907_CR4","doi-asserted-by":"publisher","unstructured":"Cand\u00e8s EJ, Wakin MB, Boyd SP (2007) Enhancing sparsity by reweighted L1 minimization. J Fourier Anal Appl 14(5):877\u2013905. https:\/\/doi.org\/10.1007\/s00041-008-9045-x","DOI":"10.1007\/s00041-008-9045-x"},{"issue":"5","key":"9907_CR5","first-page":"877","volume":"14","author":"EJ Cand\u00e8s","year":"2007","unstructured":"Cand\u00e8s EJ, Wakin MB, Boyd SP (2007) Enhancing sparsity by reweighted L1 minimization. J Fourier Anal Appl 14(5):877\u2013905","journal-title":"J Fourier Anal Appl"},{"key":"9907_CR6","unstructured":"Chen C, Tramel EW, Fowler JE (2012) Compressed-sensing recovery of images and video using multihypothesis predictions, in: IEEE 46th Signals, systems and computers, pp. 1193\u20131198."},{"issue":"8","key":"9907_CR7","doi-asserted-by":"publisher","first-page":"3618","DOI":"10.1109\/TIP.2014.2329449","volume":"23","author":"W Dong","year":"2014","unstructured":"Dong W, Shi G, Li X (2014) Compressive sensing via nonlocal low-rank regularization. IEEE Trans Image Process 23(8):3618\u20133632","journal-title":"IEEE Trans Image Process"},{"issue":"4","key":"9907_CR8","doi-asserted-by":"publisher","first-page":"1289","DOI":"10.1109\/TIT.2006.871582","volume":"52","author":"DL Donoho","year":"2006","unstructured":"Donoho DL (2006) Compressed sensing. IEEE Trans Inf Theory 52(4):1289\u20131306","journal-title":"IEEE Trans Inf Theory"},{"key":"9907_CR9","doi-asserted-by":"publisher","unstructured":"Eftekhari A, Wakin MB (2015) New analysis of manifold Embeddings and signal recovery from compressive measurements. Appl Comput Harmon Anal 39(1):67\u2013109. https:\/\/doi.org\/10.1016\/j.acha.2014.08.005","DOI":"10.1016\/j.acha.2014.08.005"},{"key":"9907_CR10","doi-asserted-by":"crossref","unstructured":"Emmanuel J. Cand\u00e8s, Wakin M B , Boyd S P, \"Enhancing Sparsity by Reweighted L1 Minimization,\" Journal of Fourier Analysis &Applications, vol. 14, no. 5, pp. 877-905, 2007.","DOI":"10.1007\/s00041-008-9045-x"},{"issue":"4","key":"9907_CR11","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1561\/2000000033","volume":"4","author":"JE Fowler","year":"2012","unstructured":"Fowler JE, Mun S, Tramel EW (2012) Block-based compressed sensing of images and video. Found Trends Signal Process 4(4):297\u2013416","journal-title":"Found Trends Signal Process"},{"key":"9907_CR12","unstructured":"Gan L (2007) Block compressed sensing of natural images, in: IEEE Proceedings of the 15th International Conference on Digital Signal Processing, pp. 403\u2013406."},{"issue":"12","key":"9907_CR13","doi-asserted-by":"publisher","first-page":"7204","DOI":"10.1109\/TIT.2012.2210860","volume":"58","author":"C Hegde","year":"2012","unstructured":"Hegde C, Baraniuk RG (2012) Signal recovery on incoherent manifolds. IEEE Trans. Inf. Theory 58(12):7204\u20137214","journal-title":"IEEE Trans. Inf. Theory"},{"key":"9907_CR14","unstructured":"Hegde C, Wakin M, Baraniuk R (2008) Random projections for manifold learning, in: Advances in neural information processing systems, pp. 641\u2013648."},{"key":"9907_CR15","doi-asserted-by":"crossref","unstructured":"Illiasdis M, Spinoulas L, Katsaggelos AK (2018) Deep fully-connected networks for video compressive sensing, Elsevier Digital Signal Processing, 72","DOI":"10.1016\/j.dsp.2017.09.010"},{"key":"9907_CR16","doi-asserted-by":"publisher","unstructured":"Kindermann S, Osher S, Jones PW (2005) Deblurring and denoising of images by nonlocal functionals. Siam Journal on Multiscale Modeling & Simulation 4(4):1091\u20131115. https:\/\/doi.org\/10.1137\/050622249","DOI":"10.1137\/050622249"},{"issue":"3","key":"9907_CR17","doi-asserted-by":"publisher","first-page":"507","DOI":"10.1007\/s10589-013-9576-1","volume":"56","author":"C Li","year":"2013","unstructured":"Li C, Yin W, Jiang H, Zhang Y (2013) An efficient augmented lagrangian method with applications to total variation minimization. Comput Optim Appl 56(3):507\u2013530","journal-title":"Comput Optim Appl"},{"issue":"5","key":"9907_CR18","doi-asserted-by":"publisher","first-page":"1042","DOI":"10.1109\/TMI.2010.2100850","volume":"30","author":"SG Lingala","year":"2011","unstructured":"Lingala SG, Hu Y, DiBella E, Jacob M (2011) Accelerated dynamic MRI exploiting sparsity and low-rank structure: k-t SLR. IEEE TransMed Imag 30(5):1042\u20131054","journal-title":"IEEE TransMed Imag"},{"key":"9907_CR19","doi-asserted-by":"crossref","unstructured":"Lu H, Li S, Liu Q et al. (2018) MF-LRTC: Multi-filters guided low-rank tensor coding for image restoration, NEUROCOMPUTING.","DOI":"10.1109\/ICIP.2017.8296653"},{"issue":"1","key":"9907_CR20","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1109\/TIP.2007.911828","volume":"17","author":"J Mairal","year":"2007","unstructured":"Mairal J, Elad M, Sapiro G (2007) Sparse representation for color image restoration. IEEE Trans Image Process 17(1):53\u201369","journal-title":"IEEE Trans Image Process"},{"key":"9907_CR21","unstructured":"Mun S, Fowler JE (2010) Block Compressed Sensing of Images Using Directional Transforms, in: IEEE 17th International Conference on Image Processing, p. 547."},{"key":"9907_CR22","doi-asserted-by":"crossref","unstructured":"Mun S, Fowler JE (2011) Residual reconstruction for block-based compressed sensing of video, in: Proc. IEEE Data Compress. Conf. (DCC), pp. 183\u2013192.","DOI":"10.1109\/DCC.2011.25"},{"key":"9907_CR23","doi-asserted-by":"publisher","unstructured":"Palangi H, Ward R, Deng L (2016) Distributed compressive sensing: a deep learning approach. IEEE Trans Signal Process 64(17):4504\u20134518. https:\/\/doi.org\/10.1109\/TSP.2016.2557301","DOI":"10.1109\/TSP.2016.2557301"},{"key":"9907_CR24","doi-asserted-by":"crossref","unstructured":"Shi W, Jiang F, Liu S et al. (2019) Scalable convolutional neural network for image compressed sensing. IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)","DOI":"10.1109\/CVPR.2019.01257"},{"key":"9907_CR25","unstructured":"Siddamal KV, Bhat SP, Saroja VS (2015) A survey on compressive sensing, in: IEEE 2nd International Conference on Electronics and Communication Systems, pp. 639\u2013643."},{"key":"9907_CR26","unstructured":"Tramel EW, Fowler JE (2011) Video compressed sensing with multihypothesis, in: Proc. IEEE Data Compress. Conf. (DCC), pp. 193\u2013202."},{"key":"9907_CR27","unstructured":"Ulyanov D, Vedaldi A, Lempitsky V (2018) Deep image prior, IEEE\/CVF conference on computer vision and pattern recognition (CVPR)"},{"key":"9907_CR28","unstructured":"Van Veen D, Jalal A, Soltanolkotabi M, et al. (2018) Compressed sensing with deep image prior and learned regularization"},{"issue":"11","key":"9907_CR29","doi-asserted-by":"publisher","first-page":"2614","DOI":"10.1016\/j.sigpro.2012.04.001","volume":"92","author":"J Xu","year":"2012","unstructured":"Xu J, Ma J, Zhang D, Zhang Y, Lin S (2012) Improved total variation minimization method for compressive sensing by intra-prediction. Signal Process 92(11):2614\u20132623","journal-title":"Signal Process"},{"key":"9907_CR30","doi-asserted-by":"publisher","unstructured":"Zhang J, Ghanem B (2018) ISTA-Net: interpretable optimization-inspired deep network for image compressive sensing. IEEE Conference on Computer Vision and Pattern Recognition:1828\u20131837. https:\/\/doi.org\/10.1109\/CVPR.2018.00196","DOI":"10.1109\/CVPR.2018.00196"},{"issue":"3","key":"9907_CR31","doi-asserted-by":"publisher","first-page":"253","DOI":"10.1137\/090746379","volume":"3","author":"X Zhang","year":"2010","unstructured":"Zhang X, Burger M, Bresson X (2010) Bregmanized nonlocal regularization for deconvolution and sparse reconstruction. SIAM J Imag Sci 3(3):253\u2013276","journal-title":"SIAM J Imag Sci"},{"issue":"3","key":"9907_CR32","doi-asserted-by":"publisher","first-page":"380","DOI":"10.1109\/JETCAS.2012.2220391","volume":"2","author":"J Zhang","year":"2012","unstructured":"Zhang J, Zhao D, Zhao C (2012) Image compressive sensing recovery via collaborative sparsity. IEEE J Emerging Sel Top Circuits Syst 2(3):380\u2013391","journal-title":"IEEE J Emerging Sel Top Circuits Syst"},{"key":"9907_CR33","doi-asserted-by":"publisher","unstructured":"Zhang J, Zhao C, Zhao D et al (2014) Image compressive sensing recovery using adaptively learned sparsifying basis via L0 minimization. Signal Process 103:114\u2013126. https:\/\/doi.org\/10.1016\/j.sigpro.2013.09.025","DOI":"10.1016\/j.sigpro.2013.09.025"},{"key":"9907_CR34","doi-asserted-by":"crossref","unstructured":"Zhang J, Zhao C, Gao W (2020) Optimization-inspired compact deep compressive sensing. IEEE Journal of Selected Topics in Signal Processing","DOI":"10.1109\/JSTSP.2020.2977507"},{"key":"9907_CR35","doi-asserted-by":"crossref","unstructured":"Zhao C, Ma S, Gao W (2014) Video compressive sensing via structured Laplacian modelling, in: Proc. IEEE Vis. Commun. Image Process. Conf. pp. 402\u2013405.","DOI":"10.1109\/VCIP.2014.7051591"},{"issue":"6","key":"9907_CR36","first-page":"1","volume":"27","author":"C Zhao","year":"2016","unstructured":"Zhao C, Ma S, Zhang J, Xiong R (2016) Video compressive sensing reconstruction via reweighted residual sparsity. IEEE Trans Circuits Syst Video Technol 27(6):1\u20131","journal-title":"IEEE Trans Circuits Syst Video Technol"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09907-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-020-09907-1\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-020-09907-1.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,2,24]],"date-time":"2021-02-24T23:46:28Z","timestamp":1614210388000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-020-09907-1"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,10,28]]},"references-count":36,"journal-issue":{"issue":"5","published-print":{"date-parts":[[2021,2]]}},"alternative-id":["9907"],"URL":"https:\/\/doi.org\/10.1007\/s11042-020-09907-1","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"value":"1380-7501","type":"print"},{"value":"1573-7721","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,10,28]]},"assertion":[{"value":"31 January 2020","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 July 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"16 September 2020","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 October 2020","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}