{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T09:54:10Z","timestamp":1743069250573,"version":"3.40.3"},"publisher-location":"Cham","reference-count":20,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031463105"},{"type":"electronic","value":"9783031463112"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023]]},"DOI":"10.1007\/978-3-031-46311-2_34","type":"book-chapter","created":{"date-parts":[[2023,10,28]],"date-time":"2023-10-28T19:01:50Z","timestamp":1698519710000},"page":"407-417","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Content-Adaptive Block Clustering for\u00a0Improving VVC Adaptive Loop Filtering"],"prefix":"10.1007","author":[{"given":"Fan","family":"Ye","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dong","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2023,10,29]]},"reference":[{"key":"34_CR1","doi-asserted-by":"crossref","unstructured":"Agustsson, E., Timofte, R.: NTIRE 2017 challenge on single image super-resolution: dataset and study. In: Computer Vision and Pattern Recognition Workshops (CVPRW) (2017)","DOI":"10.1109\/CVPRW.2017.150"},{"key":"34_CR2","unstructured":"Bjontegaard, G.: Calculation of average PSNR differences between RD-curves. VCEG-M33 (2001)"},{"key":"34_CR3","unstructured":"Boyce, J., Suehring, K., Li, X., et al.: JVET common test conditions and software reference configurations. In: JVET-J1010, San Diego (2018)"},{"issue":"10","key":"34_CR4","doi-asserted-by":"publisher","first-page":"3736","DOI":"10.1109\/TCSVT.2021.3101953","volume":"31","author":"B Bross","year":"2021","unstructured":"Bross, B., Wang, Y.K., Ye, Y., et al.: Overview of the versatile video coding (VVC) standard and its applications. IEEE Trans. Circuits Syst. Video Technol. 31(10), 3736\u20133764 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"34_CR5","unstructured":"Chen, J., Ye, Y., Kim, S.H.: Algorithm description for versatile video coding and test model 10 (VTM 10). In: Document JVET-S2002, Teleconference (2020)"},{"key":"34_CR6","unstructured":"Chiu, Y.J., Xu, L.: Adaptive (wiener) filter for video compression. In: ITU-T SG16 Contribution C437, Geneva (2008)"},{"key":"34_CR7","unstructured":"Chujoh, T., Tanizawa, A., Yamakage, T.: Adaptive loop filter for improving coding efficiency. In: ITU-T SG16 Contribution C402, Geneva (2008)"},{"key":"34_CR8","unstructured":"Chujoh, T., Tanizawa, A., Yamakage, T.: Block-based adaptive loop filter. In: VCEG-AJ13, ITU-T SG16, San Diego (2008)"},{"key":"34_CR9","unstructured":"Chujoh, T., Wada, N., Yasuda, G.: Quadtree-based adaptive loop filter. In: ITU-T SG16 Contribution C181, Geneva (2009)"},{"key":"34_CR10","unstructured":"Coban, M., L\u00e9annec, F.L., Liao, R.L., et al.: Algorithm description of enhanced compression model 7 (ECM 7). In: Document JVET-AB2025, Mainz (2022)"},{"key":"34_CR11","doi-asserted-by":"crossref","unstructured":"Erfurt, J., Lim, W.Q., Schwarz, H., et al.: Extended multiple feature-based classifications for adaptive loop filtering. APSIPA Trans. Signal Inf. Process. 8, e28 (2019)","DOI":"10.1017\/ATSIP.2019.19"},{"key":"34_CR12","doi-asserted-by":"crossref","unstructured":"Erfurt, J., Lim, W.Q., Schwarz, H., et al.: Multiple feature-based classifications adaptive loop filter. In: Proceedings IEEE Picture Coding Symposium (PCS), pp. 91\u201395 (2018)","DOI":"10.1109\/PCS.2018.8456264"},{"key":"34_CR13","unstructured":"Karczewicz, M., Chen, P., Joshi, R., et al.: Video coding technology proposal by Qualcomm Inc. In: JCTVC-A121, ITU-T SG16, Dresden (2010)"},{"issue":"10","key":"34_CR14","doi-asserted-by":"publisher","first-page":"3907","DOI":"10.1109\/TCSVT.2021.3072297","volume":"31","author":"M Karczewicz","year":"2021","unstructured":"Karczewicz, M., Hu, N., Taquet, J., et al.: VVC in-loop filters. IEEE Trans. Circuits Syst. Video Technol. 31(10), 3907\u20133925 (2021)","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"34_CR15","doi-asserted-by":"crossref","unstructured":"Karczewicz, M., Zhang, L., Chien, W.J., et al.: Geometry transformation-based adaptive in-loop filter. In: Proceedings IEEE Picture Coding Symposium (PCS), pp. 1\u20135 (2016)","DOI":"10.1109\/PCS.2016.7906346"},{"key":"34_CR16","doi-asserted-by":"publisher","first-page":"176330","DOI":"10.1109\/ACCESS.2020.3026649","volume":"8","author":"SC Lim","year":"2020","unstructured":"Lim, S.C., Kim, M., Kang, J., et al.: Subsampled sum-modified-laplacian for adaptive loop filter in versatile video coding. IEEE Access 8, 176330\u2013176342 (2020)","journal-title":"IEEE Access"},{"issue":"5","key":"34_CR17","first-page":"1","volume":"3","author":"P Mohanaiah","year":"2013","unstructured":"Mohanaiah, P., Sathyanarayana, P., GuruKumar, L.: Image texture feature extraction using GLCM approach. Int. J. Sci. Res. Publ. 3(5), 1\u20135 (2013)","journal-title":"Int. J. Sci. Res. Publ."},{"issue":"4","key":"34_CR18","doi-asserted-by":"publisher","first-page":"319","DOI":"10.3233\/IDA-2007-11402","volume":"11","author":"T Su","year":"2007","unstructured":"Su, T., Dy, J.G.: In search of deterministic methods for initializing k-means and gaussian mixture clustering. Intell. Data Anal. 11(4), 319\u2013338 (2007)","journal-title":"Intell. Data Anal."},{"key":"34_CR19","doi-asserted-by":"crossref","unstructured":"Tsai, C.Y., Chen, C.Y., Yamakage, T., et al.: Adaptive loop filtering for video coding. IEEE J. Sel. Top. Signal Process. 7(6), 934\u2013945 (2013)","DOI":"10.1109\/JSTSP.2013.2271974"},{"key":"34_CR20","unstructured":"Van Den Oord, A., Vinyals, O., et al.: Neural discrete representation learning. In: Advances in Neural Information Processing Systems, pp. 6306\u20136315 (2017)"}],"container-title":["Lecture Notes in Computer Science","Image and Graphics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-46311-2_34","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,10,28]],"date-time":"2023-10-28T19:05:39Z","timestamp":1698519939000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-46311-2_34"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031463105","9783031463112"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-46311-2_34","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"29 October 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIG","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Image and Graphics","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Nanjing","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"12","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icig2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/icig2023.csig.org.cn\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Double-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Conference Management Toolkit","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"409","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"166","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"41% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}