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引用次数: 1

摘要

我们专注于设计在噪声信道上传输的鲁棒视频压缩方案。介绍了一种多模视频编码框架,该框架能够在高压缩效率和高容错性的冲突目标之间进行优化权衡。本文从一个简单的无运动补偿的基于块的预测编码器开始,开发了鲁棒的多模视频压缩方案。所提出的多模视频编码器迭代设计算法直接最小化了总体的率失真代价。我们展示了几种传统的联合源信道编码机制可以在多模方案中合并,以进一步提高视频编码器的性能。给出了压缩基准视频序列在噪声信道条件下传输的仿真结果。他们证明了多模编码器优于传统的固定长度方法,并且可以在重建图像的PSNR中获得超过6 dB的大幅增益。
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Multimode video coding for noisy channels
We focus on the design of robust video compression schemes for transmission over noisy channels. A multimode video coding framework is introduced, which enables optimizing the tradeoff between the conflicting objectives of high compression efficiency and error resilience. The starting point is a simple block-based predictive coder, with no motion compensation, for which we develop the robust multimode video compression scheme. The proposed iterative design algorithm for multimode video coders directly minimizes the overall rate-distortion cost. We show that several conventional joint source-channel coding mechanisms can be incorporated within a multimode scheme to further enhance the video coder performance. Simulation results of compressing benchmark video sequences for transmission over noisy channel conditions are presented. They demonstrate that multimode coders outperform conventional fixed length approaches and can achieve substantial gains of more than 6 dB in PSNR of the reconstructed picture.
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Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part I Computer Analysis of Images and Patterns: 19th International Conference, CAIP 2021, Virtual Event, September 28–30, 2021, Proceedings, Part II Computer Analysis of Images and Patterns: CAIP 2019 International Workshops, ViMaBi and DL-UAV, Salerno, Italy, September 6, 2019, Proceedings Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part I Computer Analysis of Images and Patterns: 18th International Conference, CAIP 2019, Salerno, Italy, September 3–5, 2019, Proceedings, Part II
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