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Method and apparatus for applying deep learning techniques in video coding, restoration and video quality analysis (VQA)

机译:用于在视频编码、恢复和视频质量分析(VQA)中应用深度学习技术的方法和装置

摘要

Video quality analysis may be used in many multimedia transmission and communication applications, such as encoder optimization, stream selection, and/or video reconstruction. An objective VQA metric that accurately reflects the quality of processed video relative to a source unprocessed video may take into account both spatial measures and temporal, motion-based measures when evaluating the processed video. Temporal measures may include differential motion metrics indicating a difference between a frame difference of a plurality of frames of the processed video relative to that of a corresponding plurality of frames of the source video. In addition, neural networks and deep learning techniques can be used to develop additional improved VQA metrics that take into account both spatial and temporal aspects of the processed and unprocessed videos.
机译:视频质量分析可用于许多多媒体传输和通信应用,例如编码器优化、流选择和/或视频重建。客观的VQA度量准确反映了相对于源未处理视频的已处理视频的质量,在评估已处理视频时,可以考虑空间度量和基于运动的时间度量。时间度量可以包括差分运动度量,该差分运动度量指示处理视频的多个帧的帧差与源视频的相应多个帧的帧差之间的差。此外,神经网络和深度学习技术可用于开发额外的改进VQA指标,该指标考虑了已处理和未处理视频的空间和时间方面。

著录项

  • 公开/公告号US11310509B2

    专利类型

  • 公开/公告日2022-04-19

    原文格式PDF

  • 申请/专利权人 FASTVDO LLC;

    申请/专利号US202017119981

  • 申请日2020-12-11

  • 分类号H04N19/154;H04N19/172;H04N19/174;H04N19/567;H04N19/107;G06N3/08;H04N19/124;H04N19/176;G06T7/254;G06N20/10;G06T3/40;G06T5;G06T7;G06T9;H04N21/234;H04N21/2343;H04N21/236;

  • 国家 US

  • 入库时间 2022-08-25 00:33:35

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