Mizuki Murayama, Daisuke Oguro, H. Kikuchi, H. Huttunen, Yo-Sung Ho, Jaeho Shin
{"title":"基于信息理论散度的彩色图像颜色分布相似度研究","authors":"Mizuki Murayama, Daisuke Oguro, H. Kikuchi, H. Huttunen, Yo-Sung Ho, Jaeho Shin","doi":"10.1109/APSIPA.2016.7820681","DOIUrl":null,"url":null,"abstract":"The divergence similarity between two color images is presented based on the Jensen-Shannon divergence to measure the color-distribution similarity. Subjective assessment experiments were developed to obtain mean opinion scores (MOS) of test images. It was found that the divergence similarity and MOS values showed statistically significant correlations.","PeriodicalId":409448,"journal":{"name":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Color-distribution similarity by information theoretic divergence for color images\",\"authors\":\"Mizuki Murayama, Daisuke Oguro, H. Kikuchi, H. Huttunen, Yo-Sung Ho, Jaeho Shin\",\"doi\":\"10.1109/APSIPA.2016.7820681\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The divergence similarity between two color images is presented based on the Jensen-Shannon divergence to measure the color-distribution similarity. Subjective assessment experiments were developed to obtain mean opinion scores (MOS) of test images. It was found that the divergence similarity and MOS values showed statistically significant correlations.\",\"PeriodicalId\":409448,\"journal\":{\"name\":\"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)\",\"volume\":\"53 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/APSIPA.2016.7820681\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/APSIPA.2016.7820681","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Color-distribution similarity by information theoretic divergence for color images
The divergence similarity between two color images is presented based on the Jensen-Shannon divergence to measure the color-distribution similarity. Subjective assessment experiments were developed to obtain mean opinion scores (MOS) of test images. It was found that the divergence similarity and MOS values showed statistically significant correlations.