判断运动复杂度的快速运动估计算法

黄华 1; 程徽 1; 刘玎玎 2

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判断运动复杂度的快速运动估计算法

更新时间：2025-07-09

- 判断运动复杂度的快速运动估计算法
- A Fast Motion Estimation Algorithm for Motion Complexity Decision
- 西安交通大学学报 2009年43卷第10期页码：81-84+93
- 作者机构：
  
  西安交通大学电子与信息工程学院,西安,710049
- 作者简介：
- 基金信息：
  
  : 2009-02-24. 作者简介: 黄华(1980-),男,副教授. 基金项目: 国家自然科学基金资助项目(60703003)
- DOI：
  中图分类号： TN919.81
- 网络首发：2009-10-10，
  
  纸质出版：2009
- 稿件说明：
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黄华 1, 程徽 1, 刘玎玎 2. 判断运动复杂度的快速运动估计算法[J]. 西安交通大学学报, 2009,43(10):81-84+93.

A Fast Motion Estimation Algorithm for Motion Complexity Decision[J]. 2009, 43(10): 81-84+93.
黄华 1, 程徽 1, 刘玎玎 2. 判断运动复杂度的快速运动估计算法[J]. 西安交通大学学报, 2009,43(10):81-84+93. DOI：

A Fast Motion Estimation Algorithm for Motion Complexity Decision[J]. 2009, 43(10): 81-84+93. DOI：

摘要

为了提高视频压缩编码中运动估计算法的效率

提出了一种判断运动复杂度的快速运动估计算法(MC-FME算法).首先利用单帧图像的纹理信息与宏块匹配残差自适应地判断帧级运动复杂度

再利用当前宏块运动向量预测集中预测值的差异性自适应地判断宏块级运动复杂度

最后根据运动复杂度进行相应的运动估计.实验结果表明

与菱形搜索算法和分级运动估计算法相比

MC-FME算法可以在保证图像质量的前提下

匹配点数降低5%～21%

运动估计时间缩短3%～5%

从而达到加快运动估计的目的.

Abstract

To improve the performance of motion estimation(ME)

a new fast motion estimation algorithm is proposed for motion complexity decision(MC-FME). The algorithm adaptively estimates the frame-level motion complexity by using the frame texture information and the macro-block residual value at first

and then adaptively estimates the macro-block-level motion complexity by calculating the variations of predictions in the prediction set of the macro-block motion vectors. The complexity is finally used to estimate the motion. Experimental results and comparisons with the diamond search algorithm and the hierarchical motion estimation algorithm show that the proposed algorithm can get 5% to 21% reduction in the number of matched points and save 3% to 5% motion estimation time while the image quality is guaranteed.

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references

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