Tsung-Yau Huang, Po-Yen Su, Chieh-Kai Kao, Tao-Sheng Ou, Homer H. Chen
{"title":"基于率失真优化量化的视频编解码器质量改进","authors":"Tsung-Yau Huang, Po-Yen Su, Chieh-Kai Kao, Tao-Sheng Ou, Homer H. Chen","doi":"10.1109/ISM.2011.85","DOIUrl":null,"url":null,"abstract":"Conventional quantization methods consider only the distortion between original and reconstructed video as the cost of compression. Considering the time-varying nature of network bandwidth for multimedia services, we believe a video coding system can provide a better quality of experience if it takes the bit rate of the compressed bit stream into consideration as well when optimizing the quantization. In this paper we present a rate-distortion optimization approach to the quantization of video coding. This approach is able to balance between rate and distortion for quantization and enhance the overall quality of the entire coding system, with only a slight increase in computational overhead. We implement this method in H.264/AVC, and the extensive experimental data obtained under various test conditions show that the performance of the R-D optimized quantization is indeed better than the H.264 reference software.","PeriodicalId":339410,"journal":{"name":"2011 IEEE International Symposium on Multimedia","volume":"160 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Quality Improvement of Video Codec by Rate-Distortion Optimized Quantization\",\"authors\":\"Tsung-Yau Huang, Po-Yen Su, Chieh-Kai Kao, Tao-Sheng Ou, Homer H. Chen\",\"doi\":\"10.1109/ISM.2011.85\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Conventional quantization methods consider only the distortion between original and reconstructed video as the cost of compression. Considering the time-varying nature of network bandwidth for multimedia services, we believe a video coding system can provide a better quality of experience if it takes the bit rate of the compressed bit stream into consideration as well when optimizing the quantization. In this paper we present a rate-distortion optimization approach to the quantization of video coding. This approach is able to balance between rate and distortion for quantization and enhance the overall quality of the entire coding system, with only a slight increase in computational overhead. We implement this method in H.264/AVC, and the extensive experimental data obtained under various test conditions show that the performance of the R-D optimized quantization is indeed better than the H.264 reference software.\",\"PeriodicalId\":339410,\"journal\":{\"name\":\"2011 IEEE International Symposium on Multimedia\",\"volume\":\"160 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-12-05\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Symposium on Multimedia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISM.2011.85\",\"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 IEEE International Symposium on Multimedia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISM.2011.85","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Quality Improvement of Video Codec by Rate-Distortion Optimized Quantization
Conventional quantization methods consider only the distortion between original and reconstructed video as the cost of compression. Considering the time-varying nature of network bandwidth for multimedia services, we believe a video coding system can provide a better quality of experience if it takes the bit rate of the compressed bit stream into consideration as well when optimizing the quantization. In this paper we present a rate-distortion optimization approach to the quantization of video coding. This approach is able to balance between rate and distortion for quantization and enhance the overall quality of the entire coding system, with only a slight increase in computational overhead. We implement this method in H.264/AVC, and the extensive experimental data obtained under various test conditions show that the performance of the R-D optimized quantization is indeed better than the H.264 reference software.