{"title":"无线多媒体通信中基于机器学习的感知视频编码","authors":"Shengxi Li, Mai Xu, Yufan Liu, Z. Ding","doi":"10.1049/PBTE081E_CH8","DOIUrl":null,"url":null,"abstract":"We present in this chapter the advantage of applying machine-learning-based perceptual coding strategies in relieving bandwidth limitation for wireless multimedia communications. Typical video-coding standards, especially the state-of-the-art high efficiency video coding (HEVC) standard as well as recent research progress on perceptual video coding, are included in this chapter. We further demonstrate an example that minimizes the overall perceptual distortion by modeling subjective quality with machine-learning-based saliency detection. We also present several promising directions in learning-based perceptual video coding to further enhance wireless multimedia communication experience.","PeriodicalId":358911,"journal":{"name":"Applications of Machine Learning in Wireless Communications","volume":"19 1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Machine-learning-based perceptual video coding in wireless multimedia communications\",\"authors\":\"Shengxi Li, Mai Xu, Yufan Liu, Z. Ding\",\"doi\":\"10.1049/PBTE081E_CH8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present in this chapter the advantage of applying machine-learning-based perceptual coding strategies in relieving bandwidth limitation for wireless multimedia communications. Typical video-coding standards, especially the state-of-the-art high efficiency video coding (HEVC) standard as well as recent research progress on perceptual video coding, are included in this chapter. We further demonstrate an example that minimizes the overall perceptual distortion by modeling subjective quality with machine-learning-based saliency detection. We also present several promising directions in learning-based perceptual video coding to further enhance wireless multimedia communication experience.\",\"PeriodicalId\":358911,\"journal\":{\"name\":\"Applications of Machine Learning in Wireless Communications\",\"volume\":\"19 1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Applications of Machine Learning in Wireless Communications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1049/PBTE081E_CH8\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applications of Machine Learning in Wireless Communications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1049/PBTE081E_CH8","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine-learning-based perceptual video coding in wireless multimedia communications
We present in this chapter the advantage of applying machine-learning-based perceptual coding strategies in relieving bandwidth limitation for wireless multimedia communications. Typical video-coding standards, especially the state-of-the-art high efficiency video coding (HEVC) standard as well as recent research progress on perceptual video coding, are included in this chapter. We further demonstrate an example that minimizes the overall perceptual distortion by modeling subjective quality with machine-learning-based saliency detection. We also present several promising directions in learning-based perceptual video coding to further enhance wireless multimedia communication experience.