{"title":"视频压缩中最优亚像素运动补偿插值滤波器的设计","authors":"K. Minoo, D. Baylon","doi":"10.1109/DCC.2015.83","DOIUrl":null,"url":null,"abstract":"In this paper, the design of optimal temporal prediction for video coding is addressed as a quantization design problem. In the proposed framework, a codebook consisting of a set of interpolation filters is optimized to achieve rate-distortion optimality. The optimization process jointly affects two aspects of motion compensation to achieve rate distortion optimality: 1) The size of the codebook or motion vector (MV) resolution and 2) The filter coefficients for each sub-sample interpolation filter. Note that filter coefficients dictate the behavior of the interpolation filter in terms of signal-noise shaping.","PeriodicalId":313156,"journal":{"name":"2015 Data Compression Conference","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"On the Design of Optimal Sub-Pixel Motion Compensation Interpolation Filters for Video Compression\",\"authors\":\"K. Minoo, D. Baylon\",\"doi\":\"10.1109/DCC.2015.83\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, the design of optimal temporal prediction for video coding is addressed as a quantization design problem. In the proposed framework, a codebook consisting of a set of interpolation filters is optimized to achieve rate-distortion optimality. The optimization process jointly affects two aspects of motion compensation to achieve rate distortion optimality: 1) The size of the codebook or motion vector (MV) resolution and 2) The filter coefficients for each sub-sample interpolation filter. Note that filter coefficients dictate the behavior of the interpolation filter in terms of signal-noise shaping.\",\"PeriodicalId\":313156,\"journal\":{\"name\":\"2015 Data Compression Conference\",\"volume\":\"6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Data Compression Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DCC.2015.83\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Data Compression Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DCC.2015.83","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
On the Design of Optimal Sub-Pixel Motion Compensation Interpolation Filters for Video Compression
In this paper, the design of optimal temporal prediction for video coding is addressed as a quantization design problem. In the proposed framework, a codebook consisting of a set of interpolation filters is optimized to achieve rate-distortion optimality. The optimization process jointly affects two aspects of motion compensation to achieve rate distortion optimality: 1) The size of the codebook or motion vector (MV) resolution and 2) The filter coefficients for each sub-sample interpolation filter. Note that filter coefficients dictate the behavior of the interpolation filter in terms of signal-noise shaping.
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