{"title":"基于感知质量的速率失真模型","authors":"Chao Wang, X. Mou, Lei Zhang","doi":"10.1109/QOMEX.2012.6263859","DOIUrl":null,"url":null,"abstract":"Rate and distortion models (R-D models) are important for current image/video encoders. They can help encoders to find the best encoding parameters for improving encoding performance quickly and effectively. However, most of the existing R-D models are based on mean square error (MSE). For the purpose of achieving better perceptual quality in encoding, the R-D models based on perceptual distortion measurement are involuntarily needed. In this paper, we proposed a perceptual quality based R-D model for lossy image/video encoding. The experimental results show that, the proposed model can accurately describe the R-D characteristics of the sources in the context of perceptual distortion, both for whole frames and the areas inside frame.","PeriodicalId":6303,"journal":{"name":"2012 Fourth International Workshop on Quality of Multimedia Experience","volume":"111 1","pages":"74-79"},"PeriodicalIF":0.0000,"publicationDate":"2012-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A perceptual quality based rate distortion model\",\"authors\":\"Chao Wang, X. Mou, Lei Zhang\",\"doi\":\"10.1109/QOMEX.2012.6263859\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Rate and distortion models (R-D models) are important for current image/video encoders. They can help encoders to find the best encoding parameters for improving encoding performance quickly and effectively. However, most of the existing R-D models are based on mean square error (MSE). For the purpose of achieving better perceptual quality in encoding, the R-D models based on perceptual distortion measurement are involuntarily needed. In this paper, we proposed a perceptual quality based R-D model for lossy image/video encoding. The experimental results show that, the proposed model can accurately describe the R-D characteristics of the sources in the context of perceptual distortion, both for whole frames and the areas inside frame.\",\"PeriodicalId\":6303,\"journal\":{\"name\":\"2012 Fourth International Workshop on Quality of Multimedia Experience\",\"volume\":\"111 1\",\"pages\":\"74-79\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-07-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 Fourth International Workshop on Quality of Multimedia Experience\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/QOMEX.2012.6263859\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 Fourth International Workshop on Quality of Multimedia Experience","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/QOMEX.2012.6263859","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Rate and distortion models (R-D models) are important for current image/video encoders. They can help encoders to find the best encoding parameters for improving encoding performance quickly and effectively. However, most of the existing R-D models are based on mean square error (MSE). For the purpose of achieving better perceptual quality in encoding, the R-D models based on perceptual distortion measurement are involuntarily needed. In this paper, we proposed a perceptual quality based R-D model for lossy image/video encoding. The experimental results show that, the proposed model can accurately describe the R-D characteristics of the sources in the context of perceptual distortion, both for whole frames and the areas inside frame.