摘要
数字粒子图象测速技术 ( DPIV- Digital Particle- Imaging Velocimetry)已在国内外得到广泛的重视和应用 ,但目前其最大的问题是精度问题 .由于 DPIV的图象数据是用 CCD摄像机经相应的图象卡采集示踪粒子图象得到的 ,这样在实验过程中不可避免引入的噪声 (主要是示踪粒子大小、示踪粒子数量、诊断窗口大小、诊断窗口内的速度梯度和量化效果等引入的噪声 )降低了实验测量的精度 .本文应用小波变换的多分辨率特性 ,对 DPIV图象 (模拟和实际图象 )进行去噪处理 ,并与维纳去噪和中值去噪进行比较 .比较结果发现 ,小波变换能提高 DPIV测量的精度 ,因而 DPIV图象只有通过小波去噪后再进行基于互相关算法重建速度场的计算才是最精确的 .
DPIV (Digital Particle Imaging Velocimetry) has been attached importance to and applied wisely interiorly and overseas. But at present, its most difficult problem is the precision. Because the tracer particle images of DPIV are sampled by CCD and image digitizer, the noise (mainly the noise of particle image size, the size of interrogation window, local velocity gradients, the number of particles within the sampling window and quantization effects) that is imported inevitably in the process of experiment falls the precision of DPIV experiment. This paper presents the image (simulative and practical image) noise removing in DPIV based on wavelet transform whose characteristic is the multiresolution. This method is compared with image noise removing by Wiener and median filter. The result shows that image noise removing in DPIV based on wavelet transform improves the precision of DPIV experiment, and it is the most precise to rebuild the velocity field based on cross correlation after image noise removing in DPIV using wavelet transform.
出处
《中国图象图形学报（A辑）》
CSCD
2000年第3期211-215,共5页
Journal of Image and Graphics
基金
国家自然科学基金资助项目 !( 5 9876 0 3 8)
