{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T13:52:20Z","timestamp":1762005140534},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030367107"},{"type":"electronic","value":"9783030367114"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-36711-4_5","type":"book-chapter","created":{"date-parts":[[2019,12,10]],"date-time":"2019-12-10T03:03:52Z","timestamp":1575947032000},"page":"50-59","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Multi-scale Information Distillation Network for Image Super Resolution in NSCT Domain"],"prefix":"10.1007","author":[{"given":"Yu","family":"Sang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jinguang","family":"Sun","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Simiao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yanfei","family":"Peng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinjun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyang","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,12,9]]},"reference":[{"key":"5_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"184","DOI":"10.1007\/978-3-319-10593-2_13","volume-title":"Computer Vision \u2013 ECCV 2014","author":"C Dong","year":"2014","unstructured":"Dong, C., Loy, C.C., He, K., Tang, X.: Learning a deep convolutional network for image super-resolution. In: Fleet, D., Pajdla, T., Schiele, B., Tuytelaars, T. (eds.) ECCV 2014. LNCS, vol. 8692, pp. 184\u2013199. Springer, Cham (2014). \nhttps:\/\/doi.org\/10.1007\/978-3-319-10593-2_13"},{"key":"5_CR2","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1007\/978-3-319-46475-6_25","volume-title":"Computer Vision \u2013 ECCV 2016","author":"C Dong","year":"2016","unstructured":"Dong, C., Loy, C.C., Tang, X.: Accelerating the super-resolution convolutional neural network. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9906, pp. 391\u2013407. Springer, Cham (2016). \nhttps:\/\/doi.org\/10.1007\/978-3-319-46475-6_25"},{"key":"5_CR3","doi-asserted-by":"crossref","unstructured":"Kim, J., Lee, J.K., Lee, K.M.: Accurate image super-resolution using very deep convolutional networks. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1646\u20131654 (2016)","DOI":"10.1109\/CVPR.2016.182"},{"key":"5_CR4","doi-asserted-by":"crossref","unstructured":"Lim, B., Son, S., Kim, H., Nah, S., Lee, K.M.: Enhanced deep residual networks for single image super-resolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2017)","DOI":"10.1109\/CVPRW.2017.151"},{"key":"5_CR5","doi-asserted-by":"crossref","unstructured":"Kim, J., Lee, J.K., Lee, K.M.: Deeply-recursive convolutional network for image super-resolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1637\u20131645 (2016)","DOI":"10.1109\/CVPR.2016.181"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Wang, Z.W., Liu, D., Yang, J.C., Han, W., Huang, T.: Deep networks for image super-resolution with sparse prior. In: International Conference on Computer Vision (ICCV), pp. 370\u2013378 (2016)","DOI":"10.1109\/ICCV.2015.50"},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Tai, Y., Yang, J., Liu, X.M.: Image super-resolution via deep recursive residual network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3147\u20133155 (2017)","DOI":"10.1109\/CVPR.2017.298"},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Tong, T., Li, G., Liu, X., Gao, Q.Q.: Image super-resolution using dense skip connections. In: International Conference on Computer Vision (ICCV), pp. 4809\u20134817 (2017)","DOI":"10.1109\/ICCV.2017.514"},{"key":"5_CR9","doi-asserted-by":"crossref","unstructured":"Tai, Y., Yang, J., Liu, X.M., Xu, C.Y.: MemNet: a persistent memory network for image restoration. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 4539\u20134547 (2017)","DOI":"10.1109\/ICCV.2017.486"},{"key":"5_CR10","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"64","DOI":"10.1007\/978-3-030-04179-3_6","volume-title":"Neural Information Processing","author":"PA Bricman","year":"2018","unstructured":"Bricman, P.A., Ionescu, R.T.: CocoNet: a deep neural network for mapping pixel coordinates to color values. In: Cheng, L., Leung, A.C.S., Ozawa, S. (eds.) ICONIP 2018. LNCS, vol. 11302, pp. 64\u201376. Springer, Cham (2018). \nhttps:\/\/doi.org\/10.1007\/978-3-030-04179-3_6"},{"key":"5_CR11","doi-asserted-by":"crossref","unstructured":"Ahn, N., Kang, B., Sohn, K.A.: Fast, accurate, and lightweight super-resolution with cascading residual network. In: Proceedings of ECCV (2018)","DOI":"10.1007\/978-3-030-01249-6_16"},{"key":"5_CR12","doi-asserted-by":"crossref","unstructured":"Shocher, A., Cohen, N., Irani, M.: Zero-shot super-resolution using deep internal learning. In: Proceedings of CVPR (2018)","DOI":"10.1109\/CVPR.2018.00329"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Zhang, K., Zuo, W., Zhang, L.: Learning a single convolutional super-resolution network for multiple degradations. In: Proceedings of CVPR (2018)","DOI":"10.1109\/CVPR.2018.00344"},{"key":"5_CR14","doi-asserted-by":"publisher","first-page":"527","DOI":"10.1007\/978-3-030-01237-3_32","volume-title":"Computer Vision \u2013 ECCV 2018","author":"Juncheng Li","year":"2018","unstructured":"Li, J.C., Fang, F.M., Mei, K.F., Zhang, G.X.: Multi-scale residual network for image super-resolution. In: European Conference on Computer Vision (ECCV), pp. 527\u2013542 (2018)"},{"key":"5_CR15","doi-asserted-by":"crossref","unstructured":"Zhang, Y.L., Tian, Y.P., Kong, Y., Zhong, B.N., Fu, Y.: Residual dense network for image super-resolution. In: The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) (2018)","DOI":"10.1109\/CVPR.2018.00262"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Hui, Z., Wang, X.M., Gao, X.B.: Fast and accurate single image super-resolution via information distillation network. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 723\u2013731 (2018)","DOI":"10.1109\/CVPR.2018.00082"},{"key":"5_CR17","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"294","DOI":"10.1007\/978-3-030-01234-2_18","volume-title":"Computer Vision \u2013 ECCV 2018","author":"Y Zhang","year":"2018","unstructured":"Zhang, Y., Li, K., Li, K., Wang, L., Zhong, B., Fu, Y.: Image super-resolution using very deep residual channel attention networks. In: Ferrari, V., Hebert, M., Sminchisescu, C., Weiss, Y. (eds.) ECCV 2018. LNCS, vol. 11211, pp. 294\u2013310. Springer, Cham (2018). \nhttps:\/\/doi.org\/10.1007\/978-3-030-01234-2_18"},{"key":"5_CR18","doi-asserted-by":"crossref","unstructured":"Guo, T.T., Mousavi, H.S., Vu, T.H., Monga, V.: Deep wavelet prediction for image super-resolution. In: The IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 104\u2013113 (2017)","DOI":"10.1109\/CVPRW.2017.148"},{"key":"5_CR19","doi-asserted-by":"crossref","unstructured":"Guo, T.T., Mousavi, H.S., Monga, V.: Orthogonally regularized deep networks for image super-resolution. arXiv preprint \narXiv:1802.02018\n\n (2018)","DOI":"10.1109\/ICASSP.2018.8462555"},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Huang, H.B., He, R., Sun, Z.N., Tan, T.N.: Wavelet-srnet: a wavelet-based CNN for multi-scale face super resolution. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1689\u20131697 (2017)","DOI":"10.1109\/ICCV.2017.187"},{"key":"5_CR21","unstructured":"Glorot, X., Bordes, A., Bengio, Y.: Deep sparse rectifier neural networks. In: Proceedings of International Conference on Artificial Intelligence and Statistics (AISTATS), pp. 315\u2013323 (2011)"},{"key":"5_CR22","volume-title":"A Wavelet Tour of Signal Processing: The Sparse Way","author":"S Mallat","year":"2008","unstructured":"Mallat, S.: A Wavelet Tour of Signal Processing: The Sparse Way. Academic Press, Cambridge (2008)"},{"issue":"12","key":"5_CR23","doi-asserted-by":"publisher","first-page":"2091","DOI":"10.1109\/TIP.2005.859376","volume":"14","author":"MN Do","year":"2005","unstructured":"Do, M.N., Vetterli, M.: The contourlet transform: an efficient directional multiresolution image representation. IEEE Trans. Image Process. 14(12), 2091\u20132160 (2005)","journal-title":"IEEE Trans. Image Process."},{"issue":"10","key":"5_CR24","doi-asserted-by":"publisher","first-page":"3089","DOI":"10.1109\/TIP.2006.877507","volume":"15","author":"AL Cunha","year":"2006","unstructured":"Cunha, A.L., Zhou, J., Do, M.N.: The nonsubsampled contourlet transform: theory, design, and applications. IEEE Trans. Image Process. 15(10), 3089\u20133101 (2006)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"5_CR25","doi-asserted-by":"publisher","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"key":"5_CR26","doi-asserted-by":"crossref","unstructured":"Agustsson, E., Timofte, R.: Ntire 2017 challenge on single image super-resolution: dataset and study. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 126\u2013135 (2017)","DOI":"10.1109\/CVPRW.2017.150"}],"container-title":["Lecture Notes in Computer Science","Neural Information Processing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-36711-4_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,12,10]],"date-time":"2019-12-10T03:04:51Z","timestamp":1575947091000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-36711-4_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030367107","9783030367114"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-36711-4_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"9 December 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICONIP","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Neural Information Processing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2019","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12 December 2019","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2019","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iconip2019","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/ajiips.com.au\/iconip2019\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}