{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T01:48:28Z","timestamp":1760233708430,"version":"build-2065373602"},"reference-count":45,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T00:00:00Z","timestamp":1612224000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>We propose an anomaly detection based image quality assessment method which exploits the correlations between feature maps from a pre-trained Convolutional Neural Network (CNN). The proposed method encodes the intra-layer correlation through the Gram matrix and then estimates the quality score combining the average of the correlation and the output from an anomaly detection method. The latter evaluates the degree of abnormality of an image by computing a correlation similarity with respect to a dictionary of pristine images. The effectiveness of the method is tested on different benchmarking datasets (LIVE-itW, KONIQ, and SPAQ).<\/jats:p>","DOI":"10.3390\/s21030994","type":"journal-article","created":{"date-parts":[[2021,2,2]],"date-time":"2021-02-02T13:01:12Z","timestamp":1612270872000},"page":"994","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["No Reference, Opinion Unaware Image Quality Assessment by Anomaly Detection"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7989-1162","authenticated-orcid":false,"given":"Marco","family":"Leonardi","sequence":"first","affiliation":[{"name":"Department of Computer Science, Systems and Communications, University of Milano-Bicocca, 20126 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9112-0574","authenticated-orcid":false,"given":"Paolo","family":"Napoletano","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Systems and Communications, University of Milano-Bicocca, 20126 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7461-1451","authenticated-orcid":false,"given":"Raimondo","family":"Schettini","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Systems and Communications, University of Milano-Bicocca, 20126 Milan, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6269-1351","authenticated-orcid":false,"given":"Alessandro","family":"Rozza","sequence":"additional","affiliation":[{"name":"lastminute.com Group, 6830 Chiasso, Switzerland"}]}],"member":"1968","published-online":{"date-parts":[[2021,2,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"673","DOI":"10.1007\/s11760-016-1009-z","article-title":"Image quality assessment based on regions of interest","volume":"11","author":"Alaei","year":"2017","journal-title":"Signal Image Video Process."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"72420O","DOI":"10.1117\/12.806693","article-title":"Image quality assessment by preprocessing and full reference model combination","volume":"Volume 7242","author":"Bianco","year":"2009","journal-title":"Proceedings SPIE Electronic Imaging: Image Quality and System Performance VI"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/S0165-1684(98)00124-8","article-title":"Perceptual quality metrics applied to still image compression","volume":"70","author":"Eckert","year":"1998","journal-title":"Signal Process."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"283","DOI":"10.1007\/s11760-010-0200-x","article-title":"Image quality assessment based on S-CIELAB model","volume":"5","author":"He","year":"2011","journal-title":"Signal Image Video Process."},{"key":"ref_5","first-page":"669","article-title":"Perceptual criteria for image quality evaluation","volume":"110","author":"Pappas","year":"2000","journal-title":"Handbook Image Video Processing"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","article-title":"Image quality assessment: From error visibility to structural similarity","volume":"13","author":"Wang","year":"2004","journal-title":"IEEE Trans. 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