{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T04:08:16Z","timestamp":1751602096452,"version":"3.41.0"},"reference-count":31,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T00:00:00Z","timestamp":1750723200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T00:00:00Z","timestamp":1750723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the Key R&D project of Shaanxi Province","award":["Grant 2022ZDLGY01-03"],"award-info":[{"award-number":["Grant 2022ZDLGY01-03"]}]},{"name":"Science Technology Project of Weinan","award":["2021ZDYF-GYCX-150"],"award-info":[{"award-number":["2021ZDYF-GYCX-150"]}]},{"DOI":"10.13039\/501100015401","name":"Shaanxi Province Key R&D Program","doi-asserted-by":"crossref","award":["2024QY2-GJHX-33"],"award-info":[{"award-number":["2024QY2-GJHX-33"]}],"id":[{"id":"10.13039\/501100015401","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["SIViP"],"published-print":{"date-parts":[[2025,9]]},"DOI":"10.1007\/s11760-025-04382-3","type":"journal-article","created":{"date-parts":[[2025,6,24]],"date-time":"2025-06-24T09:40:00Z","timestamp":1750758000000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["No-reference image quality assessment method based on self-attention transformer encoder"],"prefix":"10.1007","volume":"19","author":[{"given":"Yuanlin","family":"Zheng","sequence":"first","affiliation":[]},{"given":"Fuqiang","family":"Yang","sequence":"additional","affiliation":[]},{"given":"Chunxia","family":"Liu","sequence":"additional","affiliation":[]},{"given":"Kaiyang","family":"Liao","sequence":"additional","affiliation":[]},{"given":"Ke","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Bangyong","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Chongjun","family":"Zhong","sequence":"additional","affiliation":[]},{"given":"Hongbo","family":"Huo","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,6,24]]},"reference":[{"issue":"6","key":"4382_CR1","doi-asserted-by":"publisher","first-page":"1868","DOI":"10.1109\/TMI.2019.2959209","volume":"39","author":"Z Liao","year":"2019","unstructured":"Liao, Z., Girgis, H., Abdi, A., et al.: On modelling label uncertainty in deep neural networks: automatic estimation of intra-observer variability in 2d echocardiography quality assessment. IEEE Trans. Med. Imaging 39(6), 1868\u20131883 (2019)","journal-title":"IEEE Trans. Med. Imaging"},{"key":"4382_CR2","doi-asserted-by":"publisher","first-page":"1008","DOI":"10.1109\/TMM.2020.2991546","volume":"23","author":"W Chen","year":"2020","unstructured":"Chen, W., Gu, K., Zhao, T., et al.: Semi-reference sonar image quality assessment based on task and visual perception. IEEE Trans. Multimedia 23, 1008\u20131020 (2020)","journal-title":"IEEE Trans. Multimedia"},{"key":"4382_CR3","doi-asserted-by":"publisher","first-page":"2279","DOI":"10.1109\/TIP.2022.3154588","volume":"31","author":"Q Jiang","year":"2022","unstructured":"Jiang, Q., Liu, Z., Gu, K., et al.: Single image super-resolution quality assessment: a real-world dataset, subjective studies, and an objective metric. IEEE Trans. Image Process. 31, 2279\u20132294 (2022)","journal-title":"IEEE Trans. Image Process."},{"key":"4382_CR4","doi-asserted-by":"publisher","first-page":"176","DOI":"10.1109\/TIP.2020.3033402","volume":"30","author":"W Liu","year":"2020","unstructured":"Liu, W., Zhou, F., Lu, T., et al.: Image defogging quality assessment: real-world database and method. IEEE Trans. Image Process. 30, 176\u2013190 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"4382_CR5","doi-asserted-by":"publisher","first-page":"4149","DOI":"10.1109\/TIP.2022.3181496","volume":"31","author":"PC Madhusudana","year":"2022","unstructured":"Madhusudana, P.C., Birkbeck, N., Wang, Y., et al.: Image quality assessment using contrastive learning. IEEE Trans. Image Process. 31, 4149\u20134161 (2022)","journal-title":"IEEE Trans. Image Process."},{"issue":"4","key":"4382_CR6","doi-asserted-by":"publisher","first-page":"1275","DOI":"10.1007\/s11760-022-02335-8","volume":"17","author":"C Liu","year":"2023","unstructured":"Liu, C., Zheng, Y., Liao, K., et al.: No-reference image quality assessment of multi-level residual feature augmentation. SIViP 17(4), 1275\u20131283 (2023)","journal-title":"SIViP"},{"key":"4382_CR7","doi-asserted-by":"publisher","first-page":"1656","DOI":"10.1109\/TIP.2023.3245991","volume":"32","author":"M Liu","year":"2023","unstructured":"Liu, M., Huang, J., Zeng, D., et al.: A Multiscale approach to deep blind image quality assessment. IEEE Trans. Image Process. 32, 1656\u20131667 (2023)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"4382_CR8","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1109\/TCSVT.2018.2886771","volume":"30","author":"W Zhang","year":"2018","unstructured":"Zhang, W., Ma, K., Yan, J., et al.: Blind image quality assessment using a deep bilinear convolutional neural network. IEEE Trans. Circuits Syst. Video Technol. 30(1), 36\u201347 (2018)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"4382_CR9","doi-asserted-by":"crossref","unstructured":"Zhu, H., Li, L., Wu, J., et al.: MetaIQA: deep meta-learning for no-reference image quality assessment. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 14143\u201314152 (2020)","DOI":"10.1109\/CVPR42600.2020.01415"},{"key":"4382_CR10","doi-asserted-by":"crossref","unstructured":"Su, S., Yan, Q., Zhu, Y., et al.: Blindly assess image quality in the wild guided by a self-adaptive hyper network. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 3667\u20133676 (2020)","DOI":"10.1109\/CVPR42600.2020.00372"},{"key":"4382_CR11","doi-asserted-by":"crossref","unstructured":"Ke, J., Wang, Q., Wang, Y., et al.: Musiq: multi-scale image quality transformer. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (CVPR), pp. 5148\u20135157 (2021)","DOI":"10.1109\/ICCV48922.2021.00510"},{"issue":"4","key":"4382_CR12","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., et al.: Image quality assessment: from error visibility to structural similarity. IEEE Trans. Image Process. 13(4), 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"issue":"2","key":"4382_CR13","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1117\/1.1455011","volume":"11","author":"BL Sankur","year":"2002","unstructured":"Sankur, B.L.: Statistical evaluation of image quality measures. J. Electron. Imaging 11(2), 206\u2013223 (2002)","journal-title":"J. Electron. Imaging"},{"key":"4382_CR14","unstructured":"Wang, Z., Simoncelli, E.P., Bovik, A.C.: Multiscale structural similarity for image quality assessment. In: The Thrity-Seventh Asilomar Conference on Signals, Systems and Computers, vol. 2, pp. 1398\u20131402 (2003)"},{"issue":"8","key":"4382_CR15","doi-asserted-by":"publisher","first-page":"3339","DOI":"10.1109\/TIP.2012.2191563","volume":"21","author":"MA Saad","year":"2012","unstructured":"Saad, M.A., Bovik, A.C., Charrier, C.: Blind image quality assessment: a natural scene statistics approach in the DCT domain. IEEE Trans. Image Process. 21(8), 3339\u20133352 (2012)","journal-title":"IEEE Trans. Image Process."},{"issue":"11","key":"4382_CR16","doi-asserted-by":"publisher","first-page":"2385","DOI":"10.1109\/TIP.2009.2025923","volume":"18","author":"MP Sampat","year":"2009","unstructured":"Sampat, M.P., Wang, Z., Gupta, S., et al.: Complex wavelet structural similarity: a new image similarity index. IEEE Trans. Image Process. 18(11), 2385\u20132401 (2009)","journal-title":"IEEE Trans. Image Process."},{"issue":"1","key":"4382_CR17","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., Muller, K.R., et al.: Deep neural networks for no-reference and full-reference image quality assessment. IEEE Trans. Image Process. 27(1), 206\u2013219 (2018)","journal-title":"IEEE Trans. Image Process."},{"key":"4382_CR18","doi-asserted-by":"crossref","unstructured":"Prashnani, E., Cai, H., Mostofi, Y., et al.: PieAPP: perceptual image-error assessment through pairwise preference. In: 2018IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1808\u20131817 (2018)","DOI":"10.1109\/CVPR.2018.00194"},{"key":"4382_CR19","doi-asserted-by":"crossref","unstructured":"Cong, H., Fu, L., Zhang, R., et al.: Image quality assessment with gradient Siamese network. In: 2022 IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), pp. 1201\u20131210 (2022)","DOI":"10.1109\/CVPRW56347.2022.00127"},{"key":"4382_CR20","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1016\/j.image.2018.11.006","volume":"71","author":"T Wang","year":"2019","unstructured":"Wang, T., Zhang, L., Jia, H.: An effective general-purpose NR-IQA model using natural scene statistics (NSS) of the luminance relative order. Signal Process. Image Commun. 71, 100\u2013109 (2019)","journal-title":"Signal Process. Image Commun."},{"key":"4382_CR21","doi-asserted-by":"publisher","first-page":"5612","DOI":"10.1109\/TIP.2020.2984879","volume":"29","author":"SVR Dendi","year":"2020","unstructured":"Dendi, S.V.R., Channappayya, S.S.: No-reference video quality assessment using natural spatiotemporal scene statistics. IEEE Trans. Image Process. 29, 5612\u20135624 (2020)","journal-title":"IEEE Trans. Image Process."},{"key":"4382_CR22","doi-asserted-by":"crossref","unstructured":"Liu, Z., et al.: Swin transformer: hierarchical vision transformer using shifted windows. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision (2021)","DOI":"10.1109\/ICCV48922.2021.00986"},{"key":"4382_CR23","doi-asserted-by":"crossref","unstructured":"He, K., et al.: Masked autoencoders are scalable vision learners. In: Proceedings of the IEEE\/CVF Conference on Computer Vision and Pattern Recognition (2022)","DOI":"10.1109\/CVPR52688.2022.01553"},{"key":"4382_CR24","doi-asserted-by":"crossref","unstructured":"Kang, L., Ye, P., Li, Y., et al.: Convolutional neural networks for no-reference image quality assessment. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp. 1733\u20131740 (2014)","DOI":"10.1109\/CVPR.2014.224"},{"key":"4382_CR25","doi-asserted-by":"crossref","unstructured":"Pan, D., Shi, P., Hou, M., et al.: Blind predicting similar quality map for image quality assessment. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 6373\u20136382 (2018)","DOI":"10.1109\/CVPR.2018.00667"},{"key":"4382_CR26","doi-asserted-by":"crossref","unstructured":"Liu, X., Van De Weijer, J., Bagdanov, A.D.R.: Learning from rankings for no-reference image quality assessment. In: Proceedings of the IEEE International Conference on Computer Vision, pp. 1040\u20131049 (2017)","DOI":"10.1109\/ICCV.2017.118"},{"key":"4382_CR27","unstructured":"Wen, W., Wu, Y., Sheng, Y., Birkbeck, N., Adsumilli, B., Wang, Y.: CP-LLM: context and Pixel Aware Large Language Model for Video Quality Assessment. arXiv:2505.16025 (2025)"},{"key":"4382_CR28","unstructured":"Li, M., et al.: Next Token Is Enough: Realistic Image Quality and Aesthetic Scoring with Multimodal Large Language Model. arXiv:2503.06141 (2025)"},{"key":"4382_CR29","unstructured":"You, Z. et al.: Teaching Large Language Models to Regress Accurate Image Quality Scores using Score Distribution. arXiv:2501.11561 (2025)"},{"key":"4382_CR30","doi-asserted-by":"crossref","unstructured":"Mitra, S., Soundararajan, R.: Vision-language model guided semi-supervised learning for no-reference video quality assessment. In: ICASSP 2025\u20132025 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE (2025)","DOI":"10.1109\/ICASSP49660.2025.10890466"},{"key":"4382_CR31","doi-asserted-by":"crossref","unstructured":"Yang, Y., Li, W.: Deep learning-based non-reference image quality assessment using vision transformer with multiscale dual branch fusion. Informatica 49(10) (2025)","DOI":"10.31449\/inf.v49i10.7148"}],"container-title":["Signal, Image and Video Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04382-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11760-025-04382-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11760-025-04382-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T14:51:34Z","timestamp":1751554294000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11760-025-04382-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,24]]},"references-count":31,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2025,9]]}},"alternative-id":["4382"],"URL":"https:\/\/doi.org\/10.1007\/s11760-025-04382-3","relation":{},"ISSN":["1863-1703","1863-1711"],"issn-type":[{"type":"print","value":"1863-1703"},{"type":"electronic","value":"1863-1711"}],"subject":[],"published":{"date-parts":[[2025,6,24]]},"assertion":[{"value":"26 February 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"1 June 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"10 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 June 2025","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"772"}}