基于兴趣区域注意模型的HEVC复杂度控制

Xin Deng, Mai Xu, Shengxi Li, Zulin Wang
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引用次数: 6

摘要

本文提出了一种新的HEVC复杂度控制方法来调整其编码复杂度。首先,建立感兴趣区域(ROI)注意力模型,根据不同区域的重要性定义不同的权重;然后,提出了基于失真复杂度优化模型的复杂度控制算法,根据最大编码单元(lcu)的权重确定其最大深度。我们可以以很小的失真损失为代价,将编码复杂度降低到给定的目标水平。最后,实验结果表明,编码复杂度可以降低到预定义目标复杂度的20%,偏差小于7%。同时,我们的方法被证明比另一种最先进的方法更好地保持ROI的质量。
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Complexity control of HEVC based on region-of-interest attention model
In this paper, we present a novel complexity control method of HEVC to adjust its encoding complexity. First, a region-of-interest (ROI) attention model is established, which defines different weights for various regions according to their importance. Then, the complexity control algorithm is proposed with a distortion-complexity optimization model, to determine the maximum depth of the largest coding units (LCUs) according to their weights. We can reduce the encoding complexity to a given target level at the cost of little distortion loss. Finally, the experimental results show that the encoding complexity can drop to a pre-defined target complexity as low as 20% with bias less than 7%. Meanwhile, our method is verified to preserve the quality of ROI better than another state-of-the-art approach.
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