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[13]A. Bruhn and J. Weickert, “Lucas-Kanade Meets Horn—Schunck:Combining Local and Global Optical Flow Methods,” International Journal of Computer Vision. 2005,61(3):211-231.

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  • 标题: 一种基于多尺度分析和非线性滤波的光流算法A Modified Optical Flow Algorithm Based on Bilateral-Filter and Multi-Scale Analysis for PIV Image Processing

    作者: 史宝成, 魏进家, 庞明军

    关键字: 光流算法, PIV, 多尺度分析Optical Flow Algorithm; PIV; Multi-Resolution Analysis

    期刊名称: 《International Journal of Fluid Dynamics》, Vol.1 No.2, 2013-06-18

    摘要: PIV后处理技术对于PIV流场实验测量的结果有着重要的影响而成为研究热点。传统的互相关算法有着许多先天缺陷,本文提出的基于多尺度分析和非线性滤波的修正光流算法能够克服这些的缺陷,该算法以多层细化理论为基础,对低分辨率序列采用同性扩散算法,而高分辨率序列采用非线性扩散方法。同时,该算法被应用到实际测量的二维向上槽道流PIV图像中,结果表明该算法对于PIV图像的后处理具有良好的性能和可靠性。 PIV post-processing techniques have a great influence on the success of flow field measurement and have aroused the researchers’ wide concern. The traditional correlation algorithms have their congenital defects. In the present study, a modified optical flow algorithm is proposed to overcome these deficiencies based on bilateral-filter and multi-resolution analysis for PIV image processing. The algorithm is designed on the basis of the principle of multilayer segments, in which the isotropic diffusion method is employed to calculate the low-resolution layer of the image and the nonlinear filtering method is used to process the high-resolution layer. This new algorithm can reduce image noise effectively and maintain the details of the image boundary. The algorithm is applied to images of actual up-channel flow, and the results also confirmed that the algorithm proposed in the present study has good performance and reliability for post-processing PIV images.

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