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Attention-based adaptive intra refresh method for robust video coding

机译:基于注意力的自适应帧内刷新方法用于鲁棒视频编码

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摘要

Intra refresh is an efficient and simple technique for suppressing temporal error propagation in video transmission over error-prone networks. However, most existing intra refresh algorithms do not make good use of the visual perceptual mechanism of the Human Visual System (HVS). This paper presents an intra refresh algorithm based on an attention model and a loss impact model. Intra refresh rates are allowed to vary for different image regions according to the HVS characteristic and the channel conditions to protect the most important macro-blocks against packet loss. A joint source-channel rate-distortion model was developed taking into account the HVS characteristic to achieve an optimal end-to-end distortion for a better subjective quality. Tests demonstrate that, for the same bit rate and packet loss rate, this method provides a much better subjective feeling than existing intra refresh methods.
机译:帧内刷新是一种有效且简单的技术,用于抑制易错网络上的视频传输中的时间错误传播。但是,大多数现有的帧内刷新算法都没有充分利用人类视觉系统(HVS)的视觉感知机制。本文提出了一种基于注意力模型和损失影响模型的帧内刷新算法。允许内部刷新率根据HVS特性和通道条件针对不同的图像区域而变化,以保护最重要的宏块免受数据包丢失的影响。考虑到HVS特性,开发了一个联合的信源-信道速率失真模型,以实现最佳的端到端失真,从而获得更好的主观质量。测试表明,对于相同的比特率和丢包率,该方法比现有的帧内刷新方法具有更好的主观感觉。

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