{"title":"解耦附加损伤和细节损失的视频质量评估","authors":"Songnan Li, Lin Ma, K. Ngan","doi":"10.1109/QoMEX.2011.6065719","DOIUrl":null,"url":null,"abstract":"In this paper, a review on existing methods of extending image quality metric to video quality metric is given. It is found that three processing steps are usually involved which include the temporal channel decomposition, temporal masking and error pooling. They are utilized to extend our previously proposed image quality metric, which separately evaluates additive impairments and detail losses, to video quality metric. The resultant algorithm is tested on subjective video database LIVE and shows a good performance in matching subjective ratings.","PeriodicalId":6441,"journal":{"name":"2011 Third International Workshop on Quality of Multimedia Experience","volume":"145 1","pages":"90-95"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":"{\"title\":\"Video quality assessment by decoupling additive impairments and detail losses\",\"authors\":\"Songnan Li, Lin Ma, K. Ngan\",\"doi\":\"10.1109/QoMEX.2011.6065719\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a review on existing methods of extending image quality metric to video quality metric is given. It is found that three processing steps are usually involved which include the temporal channel decomposition, temporal masking and error pooling. They are utilized to extend our previously proposed image quality metric, which separately evaluates additive impairments and detail losses, to video quality metric. The resultant algorithm is tested on subjective video database LIVE and shows a good performance in matching subjective ratings.\",\"PeriodicalId\":6441,\"journal\":{\"name\":\"2011 Third International Workshop on Quality of Multimedia Experience\",\"volume\":\"145 1\",\"pages\":\"90-95\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"12\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 Third International Workshop on Quality of Multimedia Experience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QoMEX.2011.6065719\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 Third International Workshop on Quality of Multimedia Experience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QoMEX.2011.6065719","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Video quality assessment by decoupling additive impairments and detail losses
In this paper, a review on existing methods of extending image quality metric to video quality metric is given. It is found that three processing steps are usually involved which include the temporal channel decomposition, temporal masking and error pooling. They are utilized to extend our previously proposed image quality metric, which separately evaluates additive impairments and detail losses, to video quality metric. The resultant algorithm is tested on subjective video database LIVE and shows a good performance in matching subjective ratings.
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