{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T06:43:52Z","timestamp":1740120232781,"version":"3.37.3"},"reference-count":40,"publisher":"World Scientific Pub Co Pte Ltd","issue":"03","funder":[{"name":"Zhejiang Provincial Science and Technology Department","award":["LGG18F010006","2018C02013"],"award-info":[{"award-number":["LGG18F010006","2018C02013"]}]},{"name":"Postdoctoral Science Foundation of Zhejiang Province","award":["ZJ20180156"],"award-info":[{"award-number":["ZJ20180156"]}]},{"name":"Zhejiang Provincial Education Department","award":["Y201840496"],"award-info":[{"award-number":["Y201840496"]}]},{"name":"foundation from Development Program of Zhejiang A & F University","award":["2018FR036"],"award-info":[{"award-number":["2018FR036"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2020,3]]},"abstract":"<jats:p> As the practical applications in other fields, high-resolution images are usually expected to provide a more accurate assessment for the air-coupled ultrasonic (ACU) characterization of wooden materials. This paper investigated the feasibility of applying single image super-resolution (SISR) methods to recover high-quality ACU images from the raw observations that were constructed directly by the on-the-shelf ACU scanners. Four state-of-the-art SISR methods were applied to the low-resolution ACU images of wood products. The reconstructed images were evaluated by visual assessment and objective image quality metrics, including peak signal-to-noise-ratio and structural similarity. Both qualitative and quantitative evaluations indicated that the substantial improvement of image quality can be yielded. The results of the experiments demonstrated the superior performance and high reproducibility of the method for generating high-quality ACU images. Sparse coding based super-resolution and super-resolution convolutional neural network (SRCNN) significantly outperformed other algorithms. SRCNN has the potential to act as an effective tool to generate higher resolution ACU images due to its flexibility. <\/jats:p>","DOI":"10.1142\/s0218001420540087","type":"journal-article","created":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T06:23:17Z","timestamp":1557814997000},"page":"2054008","source":"Crossref","is-referenced-by-count":0,"title":["Generating High-Quality Air-Coupled Ultrasonic Images for Wooden Material Characterization by Single Image Super-Resolution"],"prefix":"10.1142","volume":"34","author":[{"given":"Lujun","family":"Lin","sequence":"first","affiliation":[{"name":"Jiyang College of Zhejiang A & F University, Shaoxing 311800, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6882-0716","authenticated-orcid":false,"given":"Yiming","family":"Fang","sequence":"additional","affiliation":[{"name":"Information Engineering College, Zhejiang A & F University, Hangzhou 311300, P.\u00a0R.\u00a0China"},{"name":"Suncha Bamboo & Wood Technology Co. Ltd., Lishui 323899, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaochen","family":"Du","sequence":"additional","affiliation":[{"name":"Information Engineering College, Zhejiang A & F University, Hangzhou 311300, P.\u00a0R.\u00a0China"},{"name":"Zhejiang Provincial Key Laboratory of Forestry, Intelligent Monitoring and Information Technology, Zhejiang A & F University, Hangzhou 311300, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhu","family":"Zhou","sequence":"additional","affiliation":[{"name":"Information Engineering College, Zhejiang A & F University, Hangzhou 311300, P.\u00a0R.\u00a0China"},{"name":"Zhejiang Provincial Key Laboratory of Forestry, Intelligent Monitoring and Information Technology, Zhejiang A & F University, Hangzhou 311300, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2019,7,10]]},"reference":[{"key":"S0218001420540087BIB001","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2016.01.001"},{"key":"S0218001420540087BIB002","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.11.033"},{"key":"S0218001420540087BIB003","doi-asserted-by":"publisher","DOI":"10.1179\/2042645311Y.0000000014"},{"key":"S0218001420540087BIB004","doi-asserted-by":"publisher","DOI":"10.1007\/s002260050107"},{"key":"S0218001420540087BIB005","doi-asserted-by":"publisher","DOI":"10.1016\/j.phpro.2010.01.027"},{"key":"S0218001420540087BIB006","first-page":"49","volume-title":"15th World Conf. Nondestr. Test.","author":"Buckley J.","year":"2000"},{"key":"S0218001420540087BIB007","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2014.02.006"},{"key":"S0218001420540087BIB008","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2009.10.014"},{"key":"S0218001420540087BIB009","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10593-2_13"},{"key":"S0218001420540087BIB010","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2439281"},{"key":"S0218001420540087BIB011","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-46475-6_25"},{"key":"S0218001420540087BIB012","doi-asserted-by":"publisher","DOI":"10.1109\/TUFFC.2009.1108"},{"key":"S0218001420540087BIB013","doi-asserted-by":"publisher","DOI":"10.1016\/j.compag.2017.03.015"},{"key":"S0218001420540087BIB014","first-page":"2773","volume":"6","author":"Fang Y. M.","year":"2015","journal-title":"ICIC Express Lett. Part B: Appl."},{"key":"S0218001420540087BIB015","first-page":"355","volume":"34","author":"Fang Y. M.","year":"2017","journal-title":"Chin. J. Zhejiang A & F Univ."},{"key":"S0218001420540087BIB016","first-page":"33","volume":"55","author":"Fleming M. R.","year":"2005","journal-title":"Forest Prod. J."},{"key":"S0218001420540087BIB017","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2015.02.009"},{"key":"S0218001420540087BIB018","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-69321-5_46"},{"key":"S0218001420540087BIB019","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2010.25"},{"key":"S0218001420540087BIB020","first-page":"1","volume-title":"Int. Conf. Learn. Represent.","author":"Kingma D. P.","year":"2015"},{"key":"S0218001420540087BIB021","first-page":"1097","volume-title":"26th Annu. Conf. Neural Inf. Process. Syst.","author":"Krizhevsky A.","year":"2012"},{"key":"S0218001420540087BIB022","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2017.09.062"},{"key":"S0218001420540087BIB023","first-page":"14","volume-title":"16th World Conf. on Nondestr. Test.","author":"Marchetti B.","year":"2004"},{"key":"S0218001420540087BIB024","doi-asserted-by":"publisher","DOI":"10.1016\/j.conbuildmat.2016.02.020"},{"key":"S0218001420540087BIB025","doi-asserted-by":"publisher","DOI":"10.1007\/s00138-014-0623-4"},{"key":"S0218001420540087BIB026","doi-asserted-by":"publisher","DOI":"10.1080\/19648189.2010.9693296"},{"key":"S0218001420540087BIB027","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2014.10.012"},{"key":"S0218001420540087BIB028","doi-asserted-by":"publisher","DOI":"10.1016\/j.ultras.2015.06.013"},{"key":"S0218001420540087BIB029","doi-asserted-by":"publisher","DOI":"10.1007\/s00226-010-0357-z"},{"key":"S0218001420540087BIB030","first-page":"204","volume-title":"3rd National Conf. Adv. Technol. Electr. Electron. Syst","author":"Sane P. S.","year":"2014"},{"key":"S0218001420540087BIB031","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.09.003"},{"key":"S0218001420540087BIB032","first-page":"1","volume":"4","author":"Song J.","year":"2006","journal-title":"Int. J. Appl. Sci. Eng."},{"key":"S0218001420540087BIB033","doi-asserted-by":"publisher","DOI":"10.1007\/s00226-013-0603-2"},{"key":"S0218001420540087BIB034","first-page":"101331","volume-title":"Proc. SPIE 10133, Medical Imaging 2017: Image Processing","author":"Umehara K.","year":"2017"},{"key":"S0218001420540087BIB035","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098004"},{"key":"S0218001420540087BIB036","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2003.819861"},{"key":"S0218001420540087BIB037","first-page":"1","volume-title":"IEEE Conf. Comput. Vision Pattern Recogn","author":"Yang J. C.","year":"2008"},{"key":"S0218001420540087BIB038","doi-asserted-by":"publisher","DOI":"10.1109\/TIP.2010.2050625"},{"key":"S0218001420540087BIB039","doi-asserted-by":"publisher","DOI":"10.1109\/LSP.2017.2669333"},{"key":"S0218001420540087BIB040","doi-asserted-by":"publisher","DOI":"10.1016\/j.sigpro.2016.05.002"}],"container-title":["International Journal of Pattern Recognition and Artificial Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.worldscientific.com\/doi\/pdf\/10.1142\/S0218001420540087","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,4,8]],"date-time":"2020-04-08T09:09:19Z","timestamp":1586336959000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.worldscientific.com\/doi\/abs\/10.1142\/S0218001420540087"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,7,10]]},"references-count":40,"journal-issue":{"issue":"03","published-print":{"date-parts":[[2020,3]]}},"alternative-id":["10.1142\/S0218001420540087"],"URL":"https:\/\/doi.org\/10.1142\/s0218001420540087","relation":{},"ISSN":["0218-0014","1793-6381"],"issn-type":[{"type":"print","value":"0218-0014"},{"type":"electronic","value":"1793-6381"}],"subject":[],"published":{"date-parts":[[2019,7,10]]}}}