{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,17]],"date-time":"2025-10-17T14:04:32Z","timestamp":1760709872400,"version":"3.37.3"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"15","license":[{"start":{"date-parts":[[2019,4,5]],"date-time":"2019-04-05T00:00:00Z","timestamp":1554422400000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2019,8]]},"DOI":"10.1007\/s11042-019-7511-x","type":"journal-article","created":{"date-parts":[[2019,4,5]],"date-time":"2019-04-05T15:40:38Z","timestamp":1554478838000},"page":"21981-21998","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Bi-path network coupling for single image super-resolution"],"prefix":"10.1007","volume":"78","author":[{"given":"Yalin","family":"Yang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4717-2283","authenticated-orcid":false,"given":"Qiegen","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Minghui","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Yuhao","family":"Wang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,4,5]]},"reference":[{"key":"7511_CR1","doi-asserted-by":"crossref","unstructured":"Bevilacqua M, Roumy A, Guillemot C, AlberiMorel ML (2012) Low-complexity single-image super-resolution based on nonnegative neighbor embedding. In BMVC","DOI":"10.5244\/C.26.135"},{"issue":"12","key":"7511_CR2","doi-asserted-by":"publisher","first-page":"5334","DOI":"10.1109\/TIP.2014.2364116","volume":"23","author":"M Bevilacqua","year":"2014","unstructured":"Bevilacqua M, Roumy A, Guillemot C, Morel M-LA (2014) Single-image superresolution via linear mapping of interpolated self-examples. IEEE Trans Image Process 23(12):5334\u20135347","journal-title":"IEEE Trans Image Process"},{"issue":"6","key":"7511_CR3","doi-asserted-by":"publisher","first-page":"710","DOI":"10.1109\/TIP.2004.826093","volume":"13","author":"T Blu","year":"2004","unstructured":"Blu T, Thevenaz P, Unser M (2004) Linear interpolation revitalized. IEEE Trans Image Process 13(6):710\u2013719","journal-title":"IEEE Trans Image Process"},{"key":"7511_CR4","unstructured":"Chen Y, Li J, Xiao H et al. (2017) Dual path networks[C]\/\/Advances in Neural Information Processing Systems. 4470-4478"},{"issue":"5","key":"7511_CR5","doi-asserted-by":"publisher","first-page":"969","DOI":"10.1109\/TIP.2009.2012908","volume":"18","author":"S Dai","year":"2009","unstructured":"Dai S, Han M, Xu W, Wu Y, Gong Y, Katsaggelos AK (2009) SoftCuts: A soft edge smoothness prior for color image super-resolution. IEEE Trans Image Process 18(5):969\u2013981","journal-title":"IEEE Trans Image Process"},{"key":"7511_CR6","unstructured":"Deng J, Dong W, Socher R, Li LJ, Li K, Fei-Fei L (2009) Imagenet: A large-scale hierarchical image database, Computer Vision and Pattern Recognition 2009. CVPR 2009. IEEE Conference on, pp. 248-255"},{"key":"7511_CR7","unstructured":"Dong C, Loy CC, He K, et al. (2014) Learning a deep convolutional network for image super-resolution[C]\/\/European Conference on Computer Vision. Springer, Cham, 184-199"},{"key":"7511_CR8","unstructured":"Dong C, Loy CC, Tang X (2016) Accelerating the super-resolution convolutional neural network[C]\/\/European Conference on Computer Vision. Springer, Cham, 391-407"},{"key":"7511_CR9","unstructured":"He K, Zhang X, Ren S et al. (2015) Delving deep into rectifiers: Surpassing human-level performance on imagenet classification[C]\/\/Proceedings of the IEEE international conference on computer vision. 1026-1034"},{"key":"7511_CR10","unstructured":"He K, Zhang X, Ren S et al. (2016) Deep residual learning for image recognition[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 770-778"},{"key":"7511_CR11","doi-asserted-by":"crossref","unstructured":"Huang J, Singh A, Ahuja N (2015) Single image super-resolution from transformed self-exemplars. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.","DOI":"10.1109\/CVPR.2015.7299156"},{"issue":"2","key":"7511_CR12","first-page":"3","volume":"1","author":"G Huang","year":"2017","unstructured":"Huang G, Liu Z, Weinberger KQ et al (2017) Densely connected convolutional networks[C]. Proc IEEE Conf Comput Vis Pattern Recognit 1(2):3","journal-title":"Proc IEEE Conf Comput Vis Pattern Recognit"},{"issue":"3","key":"7511_CR13","doi-asserted-by":"publisher","first-page":"1061","DOI":"10.1109\/TIP.2011.2168416","volume":"21","author":"KW Hung","year":"2012","unstructured":"Hung KW, Siu WC (2012) Robust soft-decision interpolation using weighted least squares. IEEE Trans Image Process 21(3):1061\u20131069","journal-title":"IEEE Trans Image Process"},{"key":"7511_CR14","unstructured":"Hung KW, Siu WC (2012) Single image super-resolution using iterative Wiener filter, in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process. (ICASSP), Kyoto, Japan, Mar. 1269-1272"},{"key":"7511_CR15","unstructured":"Karras T, Aila T, Laine S, Lehtinen J (2017) Progressive growing of gans for improved quality, stability, and variation. submitted to ICLR 2018"},{"key":"7511_CR16","unstructured":"Kim J, Kwon LJ, Mu LK (2016) Accurate image super-resolution using very deep convolutional networks[C]\/\/Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 1646-1654"},{"key":"7511_CR17","unstructured":"Kim J, Kwon LJ, Mu LK (2016) Deeply-recursive convolutional network for image super-resolution[C]\/\/Proceedings of the IEEE conference on computer vision and pattern recognition. 1637-1645"},{"key":"7511_CR18","unstructured":"Kingma DP, Ba J (2014) Adam: A method for stochastic optimization[J]. arXiv preprint arXiv:1412.6980."},{"key":"7511_CR19","unstructured":"Lai WS, Huang JB, Ahuja N, et al. (2017) Deep laplacian pyramid networks for fast and accurate super-resolution[C]\/\/Proc. IEEE Conf. Comput. Vis. Pattern Recognit. 624-632"},{"key":"7511_CR20","unstructured":"Ledig C, Theis L, Husz` ar F, Caballero J, Cunningham A, Acosta A, Aitken A, Tejani A, Totz J, Wang Z et al. (2016) Photo-realistic single image super-resolution using a generative adversarial network. arXiv:1609.04802"},{"key":"7511_CR21","doi-asserted-by":"crossref","unstructured":"Lim B, Son S, Kim H et al. (2017) Enhanced deep residual networks for single image super-resolution[C]\/\/The IEEE conference on computer vision and pattern recognition (CVPR) workshops. 1(2): 4.","DOI":"10.1109\/CVPRW.2017.151"},{"issue":"2","key":"7511_CR22","first-page":"239","volume":"17","author":"H Liu","year":"2010","unstructured":"Liu H, Feng Y, Li L (2010) Multi-channel fast super-resolution image reconstruction based on matrix observation model[J]. J Harbin Inst Techn 17(2):239\u2013246","journal-title":"J Harbin Inst Techn"},{"key":"7511_CR23","unstructured":"Mao X, Shen C, Yang Y-B Image restoration using very deep convolutional encoder-decoder networks with symmetric skip connections. In NIPS 2016"},{"issue":"3","key":"7511_CR24","doi-asserted-by":"publisher","first-page":"367","DOI":"10.1007\/s10915-008-9214-8","volume":"37","author":"A Marquina","year":"2008","unstructured":"Marquina A, Osher SJ (2008) Image super-resolution by TV-regularization and Bregman iteration. J Sci Comput 37(3):367\u2013382","journal-title":"J Sci Comput"},{"key":"7511_CR25","unstructured":"Martin D, Fowlkes C, Tal D et al. (2001) A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics[C]\/\/Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference on. IEEE, 2: 416-423"},{"key":"7511_CR26","unstructured":"Ronneberger O, Fischer P, Brox T (2015) U-net: Convolutional networks for biomedical image segmentation[C]\/\/International Conference on Medical image computing and computer-assisted intervention. Springer, Cham, 234-241"},{"key":"7511_CR27","unstructured":"Schulter S, Leistner C, Bischof H (2015) Fast and accurate image upscaling with super-resolution forests[C]\/\/Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 3791-3799."},{"key":"7511_CR28","doi-asserted-by":"crossref","unstructured":"Shi W, Caballero J, Ledig C, Zhuang X, Bai W, Bhatia K, Marvao AMSM de, Dawes T, ORegan D, Rueckert D (2013) Cardiac image super-resolution with global correspondence using multi-atlas patchmatch. In MICCAI","DOI":"10.1007\/978-3-642-40760-4_2"},{"key":"7511_CR29","doi-asserted-by":"crossref","unstructured":"Szegedy C, Vanhoucke V, Ioffe S, Shlens J, Wojna Z (2016) Rethinking the inception architecture for computer vision. In CVPR","DOI":"10.1109\/CVPR.2016.308"},{"key":"7511_CR30","unstructured":"Tai Y, Yang J, Liu X et al. (2017) Memnet: A persistent memory network for image restoration[C]\/\/Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 4539-4547"},{"key":"7511_CR31","unstructured":"Timofte R, De SV, Van GL (2014) A+: Adjusted anchored neighborhood regression for fast super-resolution[C]\/\/Asian Conference on Computer Vision. Springer, Cham, 111-126"},{"key":"7511_CR32","doi-asserted-by":"crossref","unstructured":"Timofte R, Agustsson E, Van Gool L, Yang M-H, Zhang L, Lim B, Son S, Kim H, Nah S, Lee KM et al. (2017) Ntire 2017 challenge on single image super-resolution: Methods and results. In CVPRW","DOI":"10.1109\/CVPRW.2017.150"},{"key":"7511_CR33","unstructured":"Tong T, Li G, Liu X et al. (2017) Image Super-Resolution Using Dense Skip Connections[C]\/\/2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 4809-4817"},{"issue":"4","key":"7511_CR34","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang Z, Bovik AC, Sheikh HR, Simoncelli EP (2004) Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 13(4):600\u2013612","journal-title":"IEEE Trans Image Process"},{"key":"7511_CR35","doi-asserted-by":"publisher","first-page":"152","DOI":"10.1016\/j.jvcir.2018.10.028","volume":"57","author":"Y Wang","year":"2018","unstructured":"Wang Y, Liu Q, Zhou H, Wang Y (2018) Learning multi-denoising autoencoding priors for image super-resolution. J Vis Commun Image Represent 57:152\u2013162","journal-title":"J Vis Commun Image Represent"},{"issue":"5","key":"7511_CR36","first-page":"556","volume":"21","author":"R Xu","year":"2016","unstructured":"Xu R, Zhang J, Huang K (2016) Image super-resolution using two-channel convolutional neural networks[J]. J Image Graph 21(5):556\u2013564","journal-title":"J Image Graph"},{"key":"7511_CR37","unstructured":"Yang CY, Yang MH (2013) Fast direct super-resolution by simple functions[C]\/\/Computer Vision (ICCV), 2013 IEEE International Conference on. IEEE, 561-568."},{"key":"7511_CR38","unstructured":"Yang J, Wright J, Huang T, et al. (2008) Image super-resolution as sparse representation of raw image patches[C]\/\/Proc. IEEE Conf. on Computer Vision and Pattern Recognition. 1-8"},{"issue":"11","key":"7511_CR39","doi-asserted-by":"publisher","first-page":"2861","DOI":"10.1109\/TIP.2010.2050625","volume":"19","author":"J Yang","year":"2010","unstructured":"Yang J, Wright J, Huang TS et al (2010) Image super-resolution via sparse representation[J]. IEEE Trans Image Process 19(11):2861\u20132873","journal-title":"IEEE Trans Image Process"},{"key":"7511_CR40","unstructured":"Zeyde R, Elad M, Protter M (2010) On single image scale-up using sparse-representations. In Proceedings of the International Conference on Curves and Surfaces"},{"key":"7511_CR41","doi-asserted-by":"crossref","unstructured":"Zhang K, Zuo W, Zhang L (2018) Learning a single convolutional super-resolution network for multiple degradations, in Proc. IEEE Conf. Comput. Vis. Pattern Recog.","DOI":"10.1109\/CVPR.2018.00344"},{"key":"7511_CR42","doi-asserted-by":"publisher","first-page":"200","DOI":"10.1016\/j.neucom.2016.11.049","volume":"226","author":"Y Zhao","year":"2017","unstructured":"Zhao Y, Wang RG, Jia W, Wang W-M, Gao W (2017) Iterative projection reconstruction for fast and efficient image upsampling. Neurocomputing 226:200\u2013211","journal-title":"Neurocomputing"},{"issue":"1","key":"7511_CR43","doi-asserted-by":"publisher","first-page":"327","DOI":"10.1109\/TIP.2011.2162423","volume":"21","author":"W Zou","year":"2012","unstructured":"Zou W, Yuen PC (2012) Very low resolution face recognition problem[J]. IEEE Trans Image Process 21(1):327\u2013340","journal-title":"IEEE Trans Image Process"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-7511-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s11042-019-7511-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-019-7511-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,3]],"date-time":"2020-04-03T23:15:56Z","timestamp":1585955756000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s11042-019-7511-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,4,5]]},"references-count":43,"journal-issue":{"issue":"15","published-print":{"date-parts":[[2019,8]]}},"alternative-id":["7511"],"URL":"https:\/\/doi.org\/10.1007\/s11042-019-7511-x","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2019,4,5]]},"assertion":[{"value":"1 July 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"29 January 2019","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"18 March 2019","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"5 April 2019","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}