Marco V. Bernardo, A. Pinheiro, P. Fiadeiro, Manuela Pereira
{"title":"色差下的图像质量","authors":"Marco V. Bernardo, A. Pinheiro, P. Fiadeiro, Manuela Pereira","doi":"10.1145/2964908","DOIUrl":null,"url":null,"abstract":"The influence of chromatic impairments on the perceived image quality is studied in this article. Under the D65 standard illuminant, a set of hyperspectral images were represented into the CIELAB color space, and the corresponding chromatic coordinates were subdivided into clusters with the k-means algorithm. Each color cluster was shifted by a predefined chromatic impairment ΔE*ab with random direction in a*b* chromatic coordinates only. Applying impairments of 3, 6, 9, 12, and 15 in a*b* coordinates to five hyperspectral images a set of modified images was generated. Those images were shown to subjects that were asked to rank their quality based on their naturalness. The Mean Opinion Score of the subjective evaluations was computed to quantify the sensitivity to the chromatic variations. This article is also complemented with an objective evaluation of the quality using several state-of-the-art metrics and using the CIEDE2000 color difference among others. Analyzing the correlations between subjective and objective quality evaluation helps us to conclude that the proposed quality estimators based on the CIEDE2000 provide the best representation. Moreover, it was concluded that the established quality metrics only become reliable by averaging their results on each color component.","PeriodicalId":50921,"journal":{"name":"ACM Transactions on Applied Perception","volume":"120 1","pages":"6:1-6:20"},"PeriodicalIF":1.9000,"publicationDate":"2016-08-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Image Quality under Chromatic Impairments\",\"authors\":\"Marco V. Bernardo, A. Pinheiro, P. Fiadeiro, Manuela Pereira\",\"doi\":\"10.1145/2964908\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The influence of chromatic impairments on the perceived image quality is studied in this article. Under the D65 standard illuminant, a set of hyperspectral images were represented into the CIELAB color space, and the corresponding chromatic coordinates were subdivided into clusters with the k-means algorithm. Each color cluster was shifted by a predefined chromatic impairment ΔE*ab with random direction in a*b* chromatic coordinates only. Applying impairments of 3, 6, 9, 12, and 15 in a*b* coordinates to five hyperspectral images a set of modified images was generated. Those images were shown to subjects that were asked to rank their quality based on their naturalness. The Mean Opinion Score of the subjective evaluations was computed to quantify the sensitivity to the chromatic variations. This article is also complemented with an objective evaluation of the quality using several state-of-the-art metrics and using the CIEDE2000 color difference among others. Analyzing the correlations between subjective and objective quality evaluation helps us to conclude that the proposed quality estimators based on the CIEDE2000 provide the best representation. Moreover, it was concluded that the established quality metrics only become reliable by averaging their results on each color component.\",\"PeriodicalId\":50921,\"journal\":{\"name\":\"ACM Transactions on Applied Perception\",\"volume\":\"120 1\",\"pages\":\"6:1-6:20\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2016-08-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Applied Perception\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1145/2964908\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Applied Perception","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1145/2964908","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
The influence of chromatic impairments on the perceived image quality is studied in this article. Under the D65 standard illuminant, a set of hyperspectral images were represented into the CIELAB color space, and the corresponding chromatic coordinates were subdivided into clusters with the k-means algorithm. Each color cluster was shifted by a predefined chromatic impairment ΔE*ab with random direction in a*b* chromatic coordinates only. Applying impairments of 3, 6, 9, 12, and 15 in a*b* coordinates to five hyperspectral images a set of modified images was generated. Those images were shown to subjects that were asked to rank their quality based on their naturalness. The Mean Opinion Score of the subjective evaluations was computed to quantify the sensitivity to the chromatic variations. This article is also complemented with an objective evaluation of the quality using several state-of-the-art metrics and using the CIEDE2000 color difference among others. Analyzing the correlations between subjective and objective quality evaluation helps us to conclude that the proposed quality estimators based on the CIEDE2000 provide the best representation. Moreover, it was concluded that the established quality metrics only become reliable by averaging their results on each color component.
期刊介绍:
ACM Transactions on Applied Perception (TAP) aims to strengthen the synergy between computer science and psychology/perception by publishing top quality papers that help to unify research in these fields.
The journal publishes inter-disciplinary research of significant and lasting value in any topic area that spans both Computer Science and Perceptual Psychology. All papers must incorporate both perceptual and computer science components.