{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T07:26:38Z","timestamp":1740122798827,"version":"3.37.3"},"reference-count":49,"publisher":"Springer Science and Business Media LLC","issue":"13","license":[{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T00:00:00Z","timestamp":1614556800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61672118"],"award-info":[{"award-number":["61672118"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["62072062"],"award-info":[{"award-number":["62072062"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Natural Science Foundation of Chongqing, China","award":["cstc2019jcyjjqX0026"],"award-info":[{"award-number":["cstc2019jcyjjqX0026"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Multimed Tools Appl"],"published-print":{"date-parts":[[2021,5]]},"DOI":"10.1007\/s11042-021-10577-w","type":"journal-article","created":{"date-parts":[[2021,3,1]],"date-time":"2021-03-01T11:03:35Z","timestamp":1614596615000},"page":"19601-19624","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Quality-distinguishing and patch-comparing no-reference image quality assessment"],"prefix":"10.1007","volume":"80","author":[{"given":"Tao","family":"Xiang","sequence":"first","affiliation":[]},{"given":"Hongfei","family":"Xiao","sequence":"additional","affiliation":[]},{"given":"Xue","family":"Qin","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,3,1]]},"reference":[{"issue":"1","key":"10577_CR1","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/TIP.2017.2760518","volume":"27","author":"S Bosse","year":"2018","unstructured":"Bosse S, Maniry D, M\u00fcller K-R, Wiegand T, Samek W (2018) Deep neural networks for no-reference and full-reference image quality assessment. IEEE Transactions on Image Processing 27(1):206\u2013219","journal-title":"IEEE Transactions on Image Processing"},{"key":"10577_CR2","doi-asserted-by":"crossref","unstructured":"Bosse S, Maniry D, Wiegand T, Samek W (2016) A deep neural network for image quality assessment. In: IEEE international conference on image processing (ICIP), pp. 3773\u20133777","DOI":"10.1109\/ICIP.2016.7533065"},{"issue":"4","key":"10577_CR3","doi-asserted-by":"publisher","first-page":"822","DOI":"10.1016\/j.sigpro.2007.09.017","volume":"88","author":"T Brando","year":"2008","unstructured":"Brando T, Queluz MP (2008) No-reference image quality assessment based on DCT domain statistics. Signal Process 88(4):822\u2013833","journal-title":"Signal Process"},{"key":"10577_CR4","doi-asserted-by":"publisher","first-page":"6496","DOI":"10.1109\/TIP.2020.2990342","volume":"29","author":"D Chen","year":"2020","unstructured":"Chen D, Wang Y, Gao W (2020) No-reference image quality assessment: An attention driven approach. IEEE Transactions on Image Processing 29:6496\u20136506","journal-title":"IEEE Transactions on Image Processing"},{"key":"10577_CR5","doi-asserted-by":"crossref","unstructured":"Cheng Z, Takeuchi M, Katto J (2017) A pre-saliency map based blind image quality assessment via convolutional neural networks. In: IEEE international symposium on multimedia (ISM), pp. 77\u201382","DOI":"10.1109\/ISM.2017.21"},{"key":"10577_CR6","unstructured":"Ghadiyaram D, Bovik A (2015) Live in the wild image quality challenge database. http:\/\/live.ece.utexas.edu\/research\/ChallengeDB\/index.html"},{"issue":"1","key":"10577_CR7","doi-asserted-by":"publisher","first-page":"372","DOI":"10.1109\/TIP.2015.2500021","volume":"25","author":"D Ghadiyaram","year":"2016","unstructured":"Ghadiyaram D, Bovik AC (2016) Massive online crowdsourced study of subjective and objective picture quality. IEEE Transactions on Image Processing 25 (1):372\u2013387","journal-title":"IEEE Transactions on Image Processing"},{"issue":"5","key":"10577_CR8","doi-asserted-by":"publisher","first-page":"1140","DOI":"10.1109\/TMM.2017.2761993","volume":"20","author":"J Gu","year":"2018","unstructured":"Gu J, Meng G, Redi JA, Xiang S, Pan C (2018) Blind image quality assessment via vector regression and object oriented pooling. IEEE Transactions on Multimedia 20(5):1140\u20131153","journal-title":"IEEE Transactions on Multimedia"},{"issue":"11","key":"10577_CR9","doi-asserted-by":"publisher","first-page":"2505","DOI":"10.1109\/TMM.2017.2703148","volume":"19","author":"J Guan","year":"2017","unstructured":"Guan J, Shuai YI, Zeng X, Cham W K, Wang X (2017) Visual importance and distortion guided deep image quality assessment framework. IEEE Transactions on Multimedia 19(11):2505\u20132520","journal-title":"IEEE Transactions on Multimedia"},{"issue":"6","key":"10577_CR10","doi-asserted-by":"publisher","first-page":"1275","DOI":"10.1109\/TNNLS.2014.2336852","volume":"26","author":"W Hou","year":"2015","unstructured":"Hou W, Gao X, Tao D, Li X (2015) Blind image quality assessment via deep learning. IEEE Transactions on Neural Networks and Learning Systems 26(6):1275\u20131286","journal-title":"IEEE Transactions on Neural Networks and Learning Systems"},{"issue":"12","key":"10577_CR11","doi-asserted-by":"publisher","first-page":"14859","DOI":"10.1007\/s11042-017-5070-6","volume":"77","author":"S Jia","year":"2018","unstructured":"Jia S, Zhang Y (2018) Saliency-based deep convolutional neural network for no-reference image quality assessment. Multimedia Tools and Applications 77(12):14859\u201314872","journal-title":"Multimedia Tools and Applications"},{"key":"10577_CR12","unstructured":"Joshi N, Kapoor A (2011) Learning a blind measure of perceptual image quality. In: IEEE conference on computer vision and pattern recognition (CVPR), pp. 305\u2013312"},{"key":"10577_CR13","doi-asserted-by":"crossref","unstructured":"Kang L, Ye P, Li Y, Doermann D (2014) Convolutional neural networks for no-reference image quality assessment. In: IEEE conference on computer vision and pattern recognition (CVPR), pp. 1733\u20131740","DOI":"10.1109\/CVPR.2014.224"},{"issue":"1","key":"10577_CR14","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1109\/JSTSP.2016.2639328","volume":"11","author":"J Kim","year":"2017","unstructured":"Kim J, Lee S (2017) Fully deep blind image quality predictor. IEEE Journal of Selected Topics in Signal Processing 11(1):206\u2013220","journal-title":"IEEE Journal of Selected Topics in Signal Processing"},{"issue":"1","key":"10577_CR15","doi-asserted-by":"publisher","first-page":"011006","DOI":"10.1117\/1.3267105","volume":"19","author":"EC Larson","year":"2010","unstructured":"Larson EC, Chandler DM (2010) Most apparent distortion: full-reference image quality assessment and the role of strategy. Journal of Electronic Imaging 19(1):011006","journal-title":"Journal of Electronic Imaging"},{"issue":"5","key":"10577_CR16","doi-asserted-by":"publisher","first-page":"793","DOI":"10.1109\/TNN.2011.2120620","volume":"22","author":"C Li","year":"2011","unstructured":"Li C, Bovik AC, Wu X (2011) Blind image quality assessment using a general regression neural network. IEEE Transactions on Neural Networks 22(5):793\u20139","journal-title":"IEEE Transactions on Neural Networks"},{"issue":"4","key":"10577_CR17","doi-asserted-by":"publisher","first-page":"609","DOI":"10.1007\/s11760-015-0784-2","volume":"10","author":"J Li","year":"2016","unstructured":"Li J, Zou L, Yan J, Deng D, Qu T, Xie G (2016) No-reference image quality assessment using prewitt magnitude based on convolutional neural networks. SIViP 10(4):609\u2013616","journal-title":"SIViP"},{"issue":"12","key":"10577_CR18","doi-asserted-by":"publisher","first-page":"2457","DOI":"10.1109\/TMM.2016.2601028","volume":"18","author":"Q Li","year":"2016","unstructured":"Li Q, Lin W, Xu J, Fang Y (2016) Blind image quality assessment using statistical structural and luminance features. IEEE Transactions on Multimedia 18(12):2457\u20132469","journal-title":"IEEE Transactions on Multimedia"},{"key":"10577_CR19","doi-asserted-by":"publisher","first-page":"94","DOI":"10.1016\/j.neucom.2014.12.015","volume":"154","author":"Y Li","year":"2015","unstructured":"Li Y, Po L-M, Xu X, Feng L, Yuan F, Cheung C-H, Cheung K-W (2015) No-reference image quality assessment with shearlet transform and deep neural networks. Neurocomputing 154:94\u2013109","journal-title":"Neurocomputing"},{"key":"10577_CR20","doi-asserted-by":"crossref","unstructured":"Liu X, van de Weijer J, Bagdanov AD (2017) Rankiqa: Learning from rankings for no-reference image quality assessment. In: Proceedings of the IEEE international conference on computer vision, pp. 1040\u20131049","DOI":"10.1109\/ICCV.2017.118"},{"key":"10577_CR21","doi-asserted-by":"crossref","unstructured":"Lu X, Lin Z, Shen X, Mech R, Wang JZ (2015) Deep multi-patch aggregation network for image style, aesthetics, and quality estimation. In: IEEE international conference on computer vision (iccv), pp. 990\u2013998","DOI":"10.1109\/ICCV.2015.119"},{"issue":"8","key":"10577_CR22","doi-asserted-by":"publisher","first-page":"3951","DOI":"10.1109\/TIP.2017.2708503","volume":"26","author":"K Ma","year":"2017","unstructured":"Ma K, Liu W, Liu T, Wang Z, Tao D (2017) dipiq: Blind image quality assessment by learning-to-rank discriminable image pairs. IEEE Transactions on Image Processing 26(8):3951\u20133964","journal-title":"IEEE Transactions on Image Processing"},{"issue":"12","key":"10577_CR23","doi-asserted-by":"publisher","first-page":"4695","DOI":"10.1109\/TIP.2012.2214050","volume":"21","author":"A Mittal","year":"2012","unstructured":"Mittal A, Moorthy AK, Bovik AC (2012) No-reference image quality assessment in the spatial domain. IEEE Transactions on Image Processing 21(12):4695\u20134708","journal-title":"IEEE Transactions on Image Processing"},{"issue":"3","key":"10577_CR24","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1109\/LSP.2012.2227726","volume":"20","author":"A Mittal","year":"2013","unstructured":"Mittal A, Soundararajan R, Bovik AC (2013) Making a \u201ccompletely blind\u201d? image quality analyzer. IEEE Signal Processing Letters 20(3):209\u2013212","journal-title":"IEEE Signal Processing Letters"},{"issue":"5","key":"10577_CR25","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1109\/LSP.2010.2043888","volume":"17","author":"AK Moorthy","year":"2010","unstructured":"Moorthy AK, Bovik AC (2010) A two-step framework for constructing blind image quality indices. IEEE Signal Processing Letters 17(5):513\u2013516","journal-title":"IEEE Signal Processing Letters"},{"issue":"12","key":"10577_CR26","doi-asserted-by":"publisher","first-page":"3350","DOI":"10.1109\/TIP.2011.2147325","volume":"20","author":"AK Moorthy","year":"2011","unstructured":"Moorthy AK, Bovik AC (2011) Blind image quality assessment: From natural scene statistics to perceptual quality. IEEE Transactions on Image Processing 20(12):3350\u201364","journal-title":"IEEE Transactions on Image Processing"},{"key":"10577_CR27","doi-asserted-by":"crossref","unstructured":"Pan C, Xu Y, Yan Y, Gu K, Yang X (2016) Exploiting neural models for no-reference image quality assessment. In: Visual Communications and Image Processing (VCIP), pp. 1\u20134","DOI":"10.1109\/VCIP.2016.7805524"},{"key":"10577_CR28","doi-asserted-by":"crossref","unstructured":"Pan D, Shi P, Hou M, Ying Z, Fu S, Zhang Y (2018) Blind predicting similar quality map for image quality assessment. In: Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 6373\u20136382","DOI":"10.1109\/CVPR.2018.00667"},{"issue":"4","key":"10577_CR29","doi-asserted-by":"publisher","first-page":"1223","DOI":"10.1109\/TCSVT.2019.2891159","volume":"29","author":"L Po","year":"2019","unstructured":"Po L, Liu M, Yuen WYF, Li Y, Xu X, Zhou C, Wong PHW, Lau KW, Luk H (2019) A novel patch variance biased convolutional neural network for no-reference image quality assessment. IEEE Transactions on Circuits and Systems for Video Technology 29(4):1223\u20131229","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10577_CR30","doi-asserted-by":"crossref","unstructured":"Ponomarenko N, Ieremeiev O, Lukin V, Egiazarian K, Jin L, Astola J, Vozel B, Chehdi K, Carli M, Battisti F (2013) Color image database TID2013: Peculiarities and preliminary results. In: European workshop on visual information processing (EUVIP), pp. 106\u2013111","DOI":"10.1007\/978-3-319-02895-8_36"},{"issue":"6","key":"10577_CR31","doi-asserted-by":"publisher","first-page":"583","DOI":"10.1109\/LSP.2010.2045550","volume":"17","author":"MA Saad","year":"2010","unstructured":"Saad MA, Bovik AC, Charrier C (2010) A dct statistics-based blind image quality index. IEEE Signal Processing Letters 17(6):583\u2013586","journal-title":"IEEE Signal Processing Letters"},{"issue":"8","key":"10577_CR32","doi-asserted-by":"publisher","first-page":"3339","DOI":"10.1109\/TIP.2012.2191563","volume":"21","author":"MA Saad","year":"2012","unstructured":"Saad MA, Bovik AC, Charrier C (2012) Blind image quality assessment: A natural scene statistics approach in the DCT domain. IEEE Transactions on Image Processing 21(8):3339\u20133352","journal-title":"IEEE Transactions on Image Processing"},{"issue":"11","key":"10577_CR33","doi-asserted-by":"publisher","first-page":"1918","DOI":"10.1109\/TIP.2005.854492","volume":"14","author":"HR Sheikh","year":"2005","unstructured":"Sheikh HR, Bovik AC, Cormack L (2005) No-reference quality assessment using natural scene statistics: JPEG2000. IEEE Transactions on Image Processing 14(11):1918\u20131927","journal-title":"IEEE Transactions on Image Processing"},{"issue":"12","key":"10577_CR34","doi-asserted-by":"publisher","first-page":"2117","DOI":"10.1109\/TIP.2005.859389","volume":"14","author":"HR Sheikh","year":"2005","unstructured":"Sheikh HR, Bovik AC, De Veciana G (2005) An information fidelity criterion for image quality assessment using natural scene statistics. IEEE Transactions on Image Processing 14(12):2117\u20132128","journal-title":"IEEE Transactions on Image Processing"},{"key":"10577_CR35","unstructured":"Sheikh HR (2005) Live image quality assessment database release 2. http:\/\/live.ece.utexas.edu\/research\/quality"},{"key":"10577_CR36","doi-asserted-by":"crossref","unstructured":"Thung K-H, Raveendran P (2009) A survey of image quality measures. In: International conference for technical postgraduates (TECHPOS), pp. 1\u20134","DOI":"10.1109\/TECHPOS.2009.5412098"},{"key":"10577_CR37","doi-asserted-by":"crossref","unstructured":"Wang H, Zuo L, Fu J (2016) Distortion recognition for image quality assessment with convolutional neural network. In: IEEE International conference on multimedia and expo (ICME), pp. 1\u20136","DOI":"10.1109\/ICME.2016.7552936"},{"issue":"4","key":"10577_CR38","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 Transactions on Image Processing 13(4):600\u2013612","journal-title":"IEEE Transactions on Image Processing"},{"issue":"5","key":"10577_CR39","doi-asserted-by":"publisher","first-page":"1336","DOI":"10.1109\/TCYB.2017.2671898","volume":"47","author":"L Wu","year":"2017","unstructured":"Wu L, Cheng J-Z, Li S, Lei B, Wang T, Ni D (2017) FUIQA: Fetal ultrasound image quality assessment with deep convolutional networks. IEEE Transactions on Cybernetics 47(5):1336\u20131349","journal-title":"IEEE Transactions on Cybernetics"},{"issue":"11","key":"10577_CR40","doi-asserted-by":"publisher","first-page":"4850","DOI":"10.1109\/TIP.2014.2355716","volume":"23","author":"W Xue","year":"2014","unstructured":"Xue W, Mou X, Zhang L, Bovik AC, Feng X (2014) Blind image quality assessment using joint statistics of gradient magnitude and laplacian features. IEEE Transactions on Image Processing 23(11):4850\u20134862","journal-title":"IEEE Transactions on Image Processing"},{"key":"10577_CR41","doi-asserted-by":"crossref","unstructured":"Xue W, Zhang L, Mou X (2013) Learning without human scores for blind image quality assessment. In: IEEE conference on computer vision and pattern recognition (CVPR), pp. 995\u20131002","DOI":"10.1109\/CVPR.2013.133"},{"key":"10577_CR42","unstructured":"Ye P, Kumar J, Kang L, Doermann D (2012) Unsupervised feature learning framework for no-reference image quality assessment. In: IEEE conference on computer vision and pattern recognition (CVPR), pp. 1098\u20131105"},{"key":"10577_CR43","doi-asserted-by":"crossref","unstructured":"Ye P, Kumar J, Kang L, Doermann D (2013) Real-time no-reference image quality assessment based on filter learning. In: IEEE conference on computer vision and pattern recognition (CVPR), pp. 987\u2013994","DOI":"10.1109\/CVPR.2013.132"},{"issue":"8","key":"10577_CR44","doi-asserted-by":"publisher","first-page":"2378","DOI":"10.1109\/TIP.2011.2109730","volume":"20","author":"L Zhang","year":"2011","unstructured":"Zhang L, Zhang L, Mou X, Zhang D (2011) FSIM: A feature similarity index for image quality assessment. IEEE Transactions on Image Processing 20 (8):2378\u20132386","journal-title":"IEEE Transactions on Image Processing"},{"key":"10577_CR45","doi-asserted-by":"crossref","unstructured":"Zhang P, Zhou W, Wu L, Li H (2015) SOM: Semantic obviousness metric for image quality assessment. In: IEEE conference on computer vision and pattern recognition (CVPR), pp. 2394\u20132402","DOI":"10.1109\/CVPR.2015.7298853"},{"issue":"1","key":"10577_CR46","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1109\/TCSVT.2018.2886771","volume":"30","author":"W Zhang","year":"2020","unstructured":"Zhang W, Ma K, Yan J, Deng D, Wang Z (2020) Blind image quality assessment using a deep bilinear convolutional neural network. IEEE Transactions on Circuits and Systems for Video Technology 30(1):36\u201347","journal-title":"IEEE Transactions on Circuits and Systems for Video Technology"},{"key":"10577_CR47","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1016\/j.patcog.2016.01.034","volume":"59","author":"W Zhang","year":"2016","unstructured":"Zhang W, Qu C, Ma L, Guan J, Huang R (2016) Learning structure of stereoscopic image for no-reference quality assessment with convolutional neural network. Pattern Recogn 59:176\u2013187","journal-title":"Pattern Recogn"},{"key":"10577_CR48","doi-asserted-by":"publisher","first-page":"2676","DOI":"10.1109\/TIP.2019.2952010","volume":"29","author":"Y Zhang","year":"2020","unstructured":"Zhang Y, Mou X, Chandler D M (2020) Learning no-reference quality assessment of multiply and singly distorted images with big data. IEEE Transactions on Image Processing 29:2676\u20132691","journal-title":"IEEE Transactions on Image Processing"},{"key":"10577_CR49","doi-asserted-by":"crossref","unstructured":"Zuo L, Wang H, Fu J (2016) Screen content image quality assessment via convolutional neural network. In: IEEE international conference on image processing (ICIP), pp. 2082\u20132086","DOI":"10.1109\/ICIP.2016.7532725"}],"container-title":["Multimedia Tools and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10577-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11042-021-10577-w\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11042-021-10577-w.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,5,21]],"date-time":"2021-05-21T06:12:38Z","timestamp":1621577558000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11042-021-10577-w"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,3,1]]},"references-count":49,"journal-issue":{"issue":"13","published-print":{"date-parts":[[2021,5]]}},"alternative-id":["10577"],"URL":"https:\/\/doi.org\/10.1007\/s11042-021-10577-w","relation":{},"ISSN":["1380-7501","1573-7721"],"issn-type":[{"type":"print","value":"1380-7501"},{"type":"electronic","value":"1573-7721"}],"subject":[],"published":{"date-parts":[[2021,3,1]]},"assertion":[{"value":"28 November 2019","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"4 November 2020","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"20 January 2021","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 March 2021","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}