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首页> 外文会议>Broadband Multimedia Systems and Broadcasting, 2009. BMSB '09 >Buffer control in H.264/AVC applications by implementing dynamic complexity-rate-distortion analysis
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Buffer control in H.264/AVC applications by implementing dynamic complexity-rate-distortion analysis

机译：通过实现动态复杂度-速率失真分析，在H.264 / AVC应用程序中进行缓冲区控制

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摘要

In this work we present a novel optimal buffer control approach for H.264/AVC low-delay applications by dynamically allocating computational complexity (such as a number of CPU clocks) and bits for encoding each coding element (basic unit) within a video sequence, according to its predicted MAD (Mean Absolute Difference), while considering buffer size limitations (preventing underflow/overflow of the buffer) and buffer delay. Our buffer control approach is based on a computational complexity-rate-distortion (C-R-D) analysis, which adds a complexity dimension to the conventional rate-distortion (R-D) analysis. Both theoretically and experimentally, we prove that by implementing the proposed buffer control approach better results are achieved. In addition, we present an optimal buffer control method and system for implementing the proposed approach, and for controlling computational complexity and bit allocation in real-time and off-line video coding. We divide each frame into one or more basic units, wherein each basic unit consists of at least one macroblock (MB), whose contents are related to a number of coding modes. We determine how much computational complexity and bits should be allocated for encoding each basic unit, while considering buffer size limitations and buffer delay, and then we allocate a corresponding group of coding modes and a quantization step-size, according to the estimated distortion (calculated by a linear regression model) of each basic unit and according to the remaining computational complexity and bits for encoding remaining basic units. For allocating a corresponding group of coding modes and the quantization step-size, we develop computational complexity - complexity step - rate (C-I-R) and rate - quantization step-size - computational complexity (R-Q-C) models.
机译：在这项工作中，我们通过动态分配计算复杂度（例如CPU时钟数）和用于对视频序列中每个编码元素（基本单元）进行编码的位，为H.264 / AVC低延迟应用提出了一种新颖的最佳缓冲区控制方法，根据其预测的MAD（平均绝对差），同时考虑缓冲区大小限制（防止缓冲区的下溢/上溢）和缓冲区延迟。我们的缓冲区控制方法基于计算复杂度-速率-失真（C-R-D）分析，这增加了常规速率-失真（R-D）分析的复杂度。无论从理论上还是实验上，我们证明了通过实施所提出的缓冲区控制方法，可以获得更好的结果。另外，我们提出了一种最佳的缓冲器控制方法和系统，用于实现所提出的方法，并控制实时和离线视频编码中的计算复杂度和比特分配。我们将每一帧分成一个或多个基本单元，其中每个基本单元由至少一个宏块（MB）组成，其内容与多种编码模式有关。我们在考虑缓冲区大小限制和缓冲区延迟的同时确定应分配多少计算复杂度和位来编码每个基本单元，然后根据估计的失真（计算得出的值）分配相应的一组编码模式和一个量化步长（通过线性回归模型），并根据剩余的计算复杂度和用于对剩余基本单元进行编码的位。为了分配相应的一组编码模式和量化步长，我们开发了计算复杂度-复杂度步长-速率（C-I-R）和速率-量化步长-计算复杂度（R-Q-C）模型。

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