Adaptive cross-quasi-diamond search algorithm based on initial search point estimation

LIANG Yan; LIU Wen-yao

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Adaptive cross-quasi-diamond search algorithm based on initial search point estimation

更新时间：2020-08-12

- Adaptive cross-quasi-diamond search algorithm based on initial search point estimation
- Optics and Precision Engineering Vol. 13, Issue 2, Pages: 237-246(2005)
- 作者机构：
  
  天津大学精密仪器与光电子工程学院,天津 300072
- 作者简介：
- 基金信息：
- DOI：
  CLC： TP391
- Received：22 December 2004，
  
  Revised：18 March 2005，
  
  Published Online：30 April 2005，
  
  Published：30 April 2005
- 稿件说明：
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LIANG Yan, LIU Wen-yao. Adaptive cross-quasi-diamond search algorithm based on initial search point estimation[J]. Optics and precision engineering, 2005, 13(2): 237-246.
DOI：

LIANG Yan, LIU Wen-yao. Adaptive cross-quasi-diamond search algorithm based on initial search point estimation[J]. Optics and precision engineering, 2005, 13(2): 237-246. DOI：

摘要

提出一种可预测搜索起点的自适应交叉-准菱形搜索算法。根据序列图像中运动矢量的交叉-中心偏置分布特性和矢量间的时空相关性

设计了一种交叉-准菱形搜索模板

并融合搜索起点预测、半途中止准则和自适应搜索模式等技术

在保证搜索准确性的同时

大幅度提高了运动估计的速度。实验结果表明

算法对各种类型的运动序列都有很强的自适应性

其平均搜索速度是新三步法的3.56倍、四步法的3.26倍、菱形法的2.71倍

搜索准确性也优于经典的快速运动估计算法

尤其对于大运动序列

具有更明显的优势

提高了视频压缩中现有的运动估计算法的性能。

Abstract

A predictive adaptive cross-quasi-diamond search algorithm (PACQDSA) is presented. Based on the cross-center-biased motion vector distribution characteristic of the real-world sequences and high space-time correlation of adjacent blocks' motion vectors

a cross-quasi-diamond search pattern was designed

and some effective techniques were used

which are composed of the prediction of initial search point

half-stop criteria and adaptive search modes. Experiments show that the algorithm is able to fit for all types of video sequences adaptively in spite of the degree of the motions. Compared with other algorithms

it is 3.56 times faster than NTSS

3.26 times faster than FSS and 2.71 times faster than DS in average. And it is better than the traditional fast motion estimation algorithms in terms of PSNR

especially for the sequences with large motion. Therefore

the algorithm improves the performance of existing motion estimation algorithms.

关键词

Keywords

references

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