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Lagrange-based Video Encoder Optimisation to Enhance Motion Representation in the Compressed-Domain

机译:基于拉格朗日的视频编码器优化,以增强压缩域中的运动表示

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Compressed-domain content analysis enables fast content-based video applications. However, conventional encoder implementation, limited to optimising data compression, does not necessarily result in content representative compressed features. In this paper, we present a novel method for video encoder optimisation that enhances reliability of content representation in the compressed video. We propose a configurable encoder model to jointly optimise bit-rate, distortion and content representation of the encoded video. In encoder optimisation for motion estimation, we analyse the behaviour of motion representation and compression efficiency over a range of content complexities. A mathematical model to control the extent of noise in selected motion vectors is presented. We demonstrate that the compressed domain motion information can be enhanced without incurring a rate-distortion overhead. The computational overheads are marginal and can be eliminated by exploiting the inherently parallel nature of the proposed optimisation model.
机译:压缩域内容分析可实现基于内容的快速视频应用程序。但是,仅限于优化数据压缩的常规编码器实现并不一定会导致内容代表压缩特征。在本文中,我们提出了一种视频编码器优化的新方法,该方法可增强压缩视频中内容表示的可靠性。我们提出了一种可配置的编码器模型,以共同优化编码视频的比特率,失真和内容表示。在运动估计的编码器优化中,我们分析了内容复杂度范围内的运动表示行为和压缩效率。提出了控制所选运动矢量中噪声程度的数学模型。我们证明,可以在不引起速率失真开销的情况下增强压缩域运动信息。计算开销很小,可以通过利用建议的优化模型的固有并行性来消除。

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