{"title":"参考免费SSIM估计全高清视频内容","authors":"M. Ries, M. Slanina, David Mora Garcia","doi":"10.1109/RADIOELEK.2011.5936447","DOIUrl":null,"url":null,"abstract":"This paper proposes a reference-free video quality estimation method for full high definition video services based on a structural similarity index. The design of our estimator is based on an artificial neural network. To achieve this, the neural network was trained with a set of video statistical parameters extracted from the most representative video contents. Moreover, estimations with neural networks allow higher applicability and require lower processing power as known reference based methods. Finally, the achieved correlation between the calculated and the estimated structural similarity index shows a very good fit.","PeriodicalId":267447,"journal":{"name":"Proceedings of 21st International Conference Radioelektronika 2011","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Reference free SSIM estimation for full HD video content\",\"authors\":\"M. Ries, M. Slanina, David Mora Garcia\",\"doi\":\"10.1109/RADIOELEK.2011.5936447\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes a reference-free video quality estimation method for full high definition video services based on a structural similarity index. The design of our estimator is based on an artificial neural network. To achieve this, the neural network was trained with a set of video statistical parameters extracted from the most representative video contents. Moreover, estimations with neural networks allow higher applicability and require lower processing power as known reference based methods. Finally, the achieved correlation between the calculated and the estimated structural similarity index shows a very good fit.\",\"PeriodicalId\":267447,\"journal\":{\"name\":\"Proceedings of 21st International Conference Radioelektronika 2011\",\"volume\":\"23 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of 21st International Conference Radioelektronika 2011\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RADIOELEK.2011.5936447\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 21st International Conference Radioelektronika 2011","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RADIOELEK.2011.5936447","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Reference free SSIM estimation for full HD video content
This paper proposes a reference-free video quality estimation method for full high definition video services based on a structural similarity index. The design of our estimator is based on an artificial neural network. To achieve this, the neural network was trained with a set of video statistical parameters extracted from the most representative video contents. Moreover, estimations with neural networks allow higher applicability and require lower processing power as known reference based methods. Finally, the achieved correlation between the calculated and the estimated structural similarity index shows a very good fit.