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首页> 外文期刊>Journal of visual communication & image representation >Dynamic computational complexity and bit allocation for optimizing H.264/AVC video compression
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Dynamic computational complexity and bit allocation for optimizing H.264/AVC video compression

机译：动态计算复杂度和位分配，用于优化H.264 / AVC视频压缩

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摘要

In this work, we present a novel approach for optimizing H.264/AVC video compression 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). Our 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 approach for the dynamic allocation better results are achieved. We also prove that the optimal computational complexity allocation along with optimal bit allocation is better than the constant computational complexity allocation along with optimal bit allocation. In addition, we present a 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, and then 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 the 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，我们提出了一种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的每个编码元素（基本单元）进行编码的位来优化H.264 / AVC视频压缩的新颖方法。其预测的MAD（平均绝对差）。我们的方法基于计算复杂度-速率-失真（C-R-D）分析，这为传统的速率-失真（R-D）分析增加了复杂度。无论从理论上还是实验上，我们都证明了通过实施所提出的动态分配方法，可以获得更好的结果。我们还证明，最佳计算复杂度分配与最佳位分配一起优于恒定计算复杂度分配与最佳位分配一起。另外，我们提出了一种用于实现所提出的方法以及用于控制实时和离线视频编码中的计算复杂度和比特分配的方法和系统。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，然后根据每个基本单元的估计失真（由线性回归模型计算）分配相应的编码模式组和量化步长根据剩余的计算复杂度和用于编码剩余基本单元的比特。为了分配相应的编码模式组和量化步长，我们开发了计算复杂度-步长率（C-I-R）和率量化步长-计算率（R-Q-C）模型。

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