{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,27]],"date-time":"2025-07-27T07:54:41Z","timestamp":1753602881621,"version":"3.37.3"},"reference-count":35,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T00:00:00Z","timestamp":1689897600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T00:00:00Z","timestamp":1689897600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100006606","name":"Natural Science Foundation of Tianjin City","doi-asserted-by":"publisher","award":["18JCYBJC85000"],"award-info":[{"award-number":["18JCYBJC85000"]}],"id":[{"id":"10.13039\/501100006606","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Vis Comput"],"published-print":{"date-parts":[[2024,4]]},"DOI":"10.1007\/s00371-023-02970-3","type":"journal-article","created":{"date-parts":[[2023,7,21]],"date-time":"2023-07-21T16:03:04Z","timestamp":1689955384000},"page":"2667-2678","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Joint super-resolution and deblurring for low-resolution text image using two-branch neural network"],"prefix":"10.1007","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9812-169X","authenticated-orcid":false,"given":"Yuanping","family":"Zhu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hui","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Saijian","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,7,21]]},"reference":[{"key":"2970_CR1","doi-asserted-by":"publisher","unstructured":"Zhang, H., Yang, J., Zhang, Y., Nasrabadi, N.M., Huang, T.S.: Close the loop: joint blind image restoration and recognition with sparse representation prior. In: 2011 International Conference on Computer Vision, pp. 770\u2013777 (2011). https:\/\/doi.org\/10.1109\/ICCV.2011.6126315","DOI":"10.1109\/ICCV.2011.6126315"},{"key":"2970_CR2","doi-asserted-by":"publisher","unstructured":"Li, J., Liang, X., Wei, Y., Xu, T., Feng, J., Yan, S.: Perceptual generative adversarial networks for small object detection. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1222\u20131230 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.211","DOI":"10.1109\/CVPR.2017.211"},{"key":"2970_CR3","doi-asserted-by":"publisher","unstructured":"Kupyn, O., Budzan, V., Mykhailych, M., Mishkin, D., Matas, J.: Deblurgan: blind motion deblurring using conditional adversarial networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8183\u20138192 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00854","DOI":"10.1109\/CVPR.2018.00854"},{"key":"2970_CR4","doi-asserted-by":"publisher","unstructured":"Wang, X., Yu, K., Wu, S., Gu, J., Liu, Y., Dong, C., Qiao, Y., Loy, C.C.: ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks: Munich, Germany, September 8\u201314, 2018. Proceedings, Part (2019). https:\/\/doi.org\/10.1007\/978-3-030-11021-5_5","DOI":"10.1007\/978-3-030-11021-5_5"},{"issue":"11","key":"2970_CR5","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, T.S., Ma, Y.: Image super-resolution via sparse representation. IEEE Trans Image Process. 19(11), 2861\u20132873 (2010). https:\/\/doi.org\/10.1109\/TIP.2010.2050625","journal-title":"IEEE Trans Image Process."},{"key":"2970_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.image.2020.115805","volume":"83","author":"X Li","year":"2020","unstructured":"Li, X., Cao, G., Zhang, Y., Shafique, A., Fu, P.: Combining synthesis sparse with analysis sparse for single image super-resolution. Signal Process. Image Commun. 83, 115805 (2020). https:\/\/doi.org\/10.1016\/j.image.2020.115805","journal-title":"Signal Process. Image Commun."},{"key":"2970_CR7","doi-asserted-by":"publisher","unstructured":"Yoon, Y., Jeon, HG., Yoo, D., et al.: Learning a deep convolutional network for light-field image super-resolution. In: IEEE International Conference on Computer Vision Workshop. IEEE (2015). https:\/\/doi.org\/10.1109\/ICCVW.2015.17","DOI":"10.1109\/ICCVW.2015.17"},{"key":"2970_CR8","doi-asserted-by":"publisher","unstructured":"Huang, J.B., Singh, A., Ahuja, N.: Single image super-resolution from transformed self-exemplars. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 5197\u20135206 (2015). https:\/\/doi.org\/10.1109\/CVPR.2015.7299156","DOI":"10.1109\/CVPR.2015.7299156"},{"key":"2970_CR9","doi-asserted-by":"publisher","unstructured":"Yoon, Y., Jeon, HG., Yoo, D., et al.: Learning a deep convolutional network for light-field image super-resolution. In: IEEE International Conference on Computer Vision Workshop. IEEE (2015). https:\/\/doi.org\/10.1109\/TPAMI.2015.2439281","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"2970_CR10","doi-asserted-by":"publisher","unstructured":"Kim, J., Kwon Lee, J., Mu Lee, K.: Accurate image super-resolution using very deep convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1646\u20131654. (2016). https:\/\/doi.org\/10.1109\/CVPR.2016.182","DOI":"10.1109\/CVPR.2016.182"},{"key":"2970_CR11","doi-asserted-by":"publisher","unstructured":"Chen, J., Li, B., Xue, X.:. Scene Text Telescope: Text-Focused Scene Image Super-Resolution, pp. 12021\u201312030 (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.01185","DOI":"10.1109\/CVPR46437.2021.01185"},{"key":"2970_CR12","doi-asserted-by":"publisher","first-page":"4367","DOI":"10.1007\/s10489-020-02116-1","volume":"51","author":"Y Chen","year":"2021","unstructured":"Chen, Y., Liu, L., Phonevilay, V., et al.: Image super-resolution reconstruction based on feature map attention mechanism. Appl. Intell. 51, 4367\u20134380 (2021). https:\/\/doi.org\/10.1007\/s10489-020-02116-1","journal-title":"Appl. Intell."},{"key":"2970_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/s00371-023-02795-0","author":"Y Chen","year":"2023","unstructured":"Chen, Y., Xia, R., Yang, K., et al.: MFFN: image super-resolution via multi-level features fusion network. Vis. Comput. (2023). https:\/\/doi.org\/10.1007\/s00371-023-02795-0","journal-title":"Vis. Comput."},{"key":"2970_CR14","unstructured":"Harmeling, S., Michael, H., Sch\u00f6lkopf, B.: Space-variant single-image blind deconvolution for removing camera shake. In: Advances in Neural Information Processing Systems, pp. 829\u2013837 (2010)"},{"key":"2970_CR15","doi-asserted-by":"publisher","unstructured":"Li, X., Zheng, S., Jia, J.: Unnatural L0 sparse representation for natural image deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 1107\u20131114 (2013). https:\/\/doi.org\/10.1109\/CVPR.2013.147","DOI":"10.1109\/CVPR.2013.147"},{"key":"2970_CR16","doi-asserted-by":"publisher","unstructured":"Tao, X., Gao, H., Shen, X., Wang, J., Jia, J.: Scale-recurrent network for deep image deblurring. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 8174\u20138182 (2018). https:\/\/doi.org\/10.1109\/CVPR.2018.00853","DOI":"10.1109\/CVPR.2018.00853"},{"key":"2970_CR17","doi-asserted-by":"publisher","first-page":"281","DOI":"10.1007\/s00371-021-02329-6","volume":"39","author":"D Hu","year":"2023","unstructured":"Hu, D., Tan, J., Zhang, L., et al.: Image deblurring based on enhanced salient edge selection. Vis. Comput. 39, 281\u2013296 (2023). https:\/\/doi.org\/10.1007\/s00371-021-02329-6","journal-title":"Vis. Comput."},{"key":"2970_CR18","doi-asserted-by":"publisher","unstructured":"Park, H., Lee, K.M.: Joint Estimation of Camera Pose, Depth, Deblurring, and Super-Resolution from a Blurred Image Sequence, pp. 4613\u20134621 (2017). https:\/\/doi.org\/10.1109\/ICCV.2017.494","DOI":"10.1109\/ICCV.2017.494"},{"key":"2970_CR19","doi-asserted-by":"publisher","unstructured":"Yamaguchi, T., Fukuda, H., Furukawa, R., Kawasaki, H., Sturm, P.: Video deblurring and super-resolution technique for multiple moving objects. In: Asian Conference on Computer Vision, pp. 127\u2013140. Springer, Berlin (2010). https:\/\/doi.org\/10.1007\/978-3-642-19282-1_11","DOI":"10.1007\/978-3-642-19282-1_11"},{"key":"2970_CR20","doi-asserted-by":"publisher","unstructured":"Lumentut, J., Park, I.: Deep neural network for joint light field deblurring and super-resolution, vol. 95 (2020). https:\/\/doi.org\/10.1117\/12.2566962","DOI":"10.1117\/12.2566962"},{"key":"2970_CR21","doi-asserted-by":"publisher","unstructured":"Niu, W., Zhang, K., Luo, W., Zhong, Y. Blind motion deblurring super-resolution: when dynamic spatio-temporal learning meets static image understanding. IEEE Trans. Image Process. (2021), https:\/\/doi.org\/10.1109\/TIP.2021.3101402","DOI":"10.1109\/TIP.2021.3101402"},{"key":"2970_CR22","unstructured":"Zhang, X., Dong, H., Hu, Z., Lai, W.S., Wang, F., Yang, M.H.: Gated fusion network for joint image deblurring and super-resolution. arXiv preprint arXiv:1807.10806 (2018)"},{"key":"2970_CR23","doi-asserted-by":"publisher","unstructured":"Xu, X., Sun, D., Pan, J., Zhang, Y., Pfifister, H., Yang, M.H.: Learning to super-resolve blurry face and text images. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 251\u2013260 (2017). https:\/\/doi.org\/10.1109\/ICCV.2017.36","DOI":"10.1109\/ICCV.2017.36"},{"key":"2970_CR24","doi-asserted-by":"publisher","unstructured":"Xing, W., Egiazarian, K.: End-to-End Learning for Joint Image Demosaicing. Denoising and super-resolution, pp. 3506\u20133515 (2021). https:\/\/doi.org\/10.1109\/CVPR46437.2021.00351","DOI":"10.1109\/CVPR46437.2021.00351"},{"key":"2970_CR25","doi-asserted-by":"publisher","unstructured":"Zhang, X., Wang, F., Dong, H., Guo, Y.: A deep dual-branch networks for joint blind motion deblurring and super-resolution. In: Proceedings of the 2nd International Conference on Vision, Image and Signal Processing (ICVISP 2018). Association for Computing Machinery, New York, NY, USA, Article 1, pp. 1\u20136 (2018). https:\/\/doi.org\/10.1145\/3271553.3271554","DOI":"10.1145\/3271553.3271554"},{"key":"2970_CR26","doi-asserted-by":"publisher","unstructured":"Odena, A., Dumoulin, V., Olah, C.: Deconvolution and Checkerboard Artifacts[EB\/OL] (2016). https:\/\/doi.org\/10.23915\/distill.00003","DOI":"10.23915\/distill.00003"},{"key":"2970_CR27","doi-asserted-by":"publisher","unstructured":"Liu, Z., Yeh, R., Tang, X., Liu, Y., Agarwala, A.: Video frame synthesis using deep voxel flow. In ICCV. IEEE (2017). https:\/\/doi.org\/10.1109\/ICCV.2017.478","DOI":"10.1109\/ICCV.2017.478"},{"key":"2970_CR28","doi-asserted-by":"publisher","unstructured":"Su, S., Delbracio, M., Wang, J., Sapiro, G., Heidrich, W., Wang, O.: Deep video deblurring for hand-held cameras, pp. 1279\u20131288 (2017). https:\/\/doi.org\/10.1109\/CVPR.2017.33","DOI":"10.1109\/CVPR.2017.33"},{"key":"2970_CR29","doi-asserted-by":"publisher","unstructured":"Kingma, D., Ba, J.: Adam: a method for stochastic optimization. Computer Science (2014). https:\/\/doi.org\/10.48550\/arXiv.1412.6980","DOI":"10.48550\/arXiv.1412.6980"},{"key":"2970_CR30","doi-asserted-by":"publisher","unstructured":"Lim, B., Son, S., Kim, H., Nah, S., Mu Lee, K.: Enhanced deep residual networks for single image super-resolution. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 136\u2013144 (2017). https:\/\/doi.org\/10.1109\/CVPRW.2017.151","DOI":"10.1109\/CVPRW.2017.151"},{"key":"2970_CR31","doi-asserted-by":"publisher","unstructured":"Ledig, C., et al.: Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA, pp. 105\u2013114 (2017). https:\/\/doi.org\/10.48550\/arXiv.1609.04802","DOI":"10.48550\/arXiv.1609.04802"},{"issue":"9","key":"2970_CR32","doi-asserted-by":"publisher","first-page":"1904","DOI":"10.1109\/TPAMI.2015.2389824","volume":"37","author":"K He","year":"2015","unstructured":"He, K., et al.: Spatial pyramid pooling in deep convolutional networks for visual recognition. IEEE Trans. Pattern Anal. Mach. Intell. 37(9), 1904\u20131916 (2015). https:\/\/doi.org\/10.1109\/TPAMI.2015.2389824","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"2970_CR33","doi-asserted-by":"publisher","unstructured":"He, K., Zhang, X., Ren, S., et al.: Delving deep into rectifiers: surpassing human-level performance on ImageNet classification. In: Proceedings of the 2015 IEEE International Conference on Computer Vision. Piscataway: IEEE, pp. 1026\u20131034 (2015). https:\/\/doi.org\/10.1109\/ICCV.2015.123","DOI":"10.1109\/ICCV.2015.123"},{"key":"2970_CR34","doi-asserted-by":"publisher","unstructured":"Ma, J., Liang, Z., Zhang, L.: A text attention network for spatial deformation robust scene text image super-resolution (2022). https:\/\/doi.org\/10.1109\/CVPR52688.2022.00582","DOI":"10.1109\/CVPR52688.2022.00582"},{"key":"2970_CR35","doi-asserted-by":"publisher","unstructured":"Hradi\u0161, M., Kotera, J., Zemc\u0131k, P., \u0161roubek, F.: Convolutional neural networks for direct text deblurring. In: Proceedings of BMVC, vol. 10, p. 2 (2015). https:\/\/doi.org\/10.5244\/C.29.6","DOI":"10.5244\/C.29.6"}],"container-title":["The Visual Computer"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-02970-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00371-023-02970-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00371-023-02970-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,5]],"date-time":"2024-04-05T17:11:21Z","timestamp":1712337081000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00371-023-02970-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,7,21]]},"references-count":35,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2024,4]]}},"alternative-id":["2970"],"URL":"https:\/\/doi.org\/10.1007\/s00371-023-02970-3","relation":{},"ISSN":["0178-2789","1432-2315"],"issn-type":[{"type":"print","value":"0178-2789"},{"type":"electronic","value":"1432-2315"}],"subject":[],"published":{"date-parts":[[2023,7,21]]},"assertion":[{"value":"13 June 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 July 2023","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"}},{"value":"The study complies with all ethical standards.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}