基于模型的连续运动矢量估值算法

Model Based Consecutive Motion Vector Estimation Algorithm

文中首先简述数字粒子图像测流体速度场ＤｉｇｉｔａｌＰａｒｔｉｃｌｅＩｍａｇｅＶｅｌｏｃｉｍｅｔｒｙ（ＤＰＩＶ）的原理以及现有的处理ＤＰＩＶ的算法思想，详细地分析这些算法的优缺点．为了克服现存算法在应用中暴露出来的共同缺陷．本文提出了一种新的处理ＤＰＩＶ序列图像的算法———基于模型的连续运动矢量估值算法．该算法充分利用图像的整体信息获得速度场的基本约束，同时根据流场的物理性质获得速度场基于模型的约束，以求得流场被测截面图像中每个像素点处运动的精确解．

In this paper the principle and the conventional algorithms of Digital Particle Image Velocimetry (DPIV) are summarized firstly,then the advantages and disadvantages of these algorithms are analyzed in detail.In order to overcome these defaults a new idea named model based consecutive motion vector estimation algorithm is proposed.The new algorithm fully employs the global information of sequential gray images and the physics property of flow field to get the precise velocity vector at each pixel.