摘要
根据气液泡状流三维特征参数高精度测量需求,针对高速摄影法采集气液两相流图像带来的噪声特性,提出双阈值小波去噪方法实现气液两相流多气泡图像去噪。基于硬阈值与软阈值的理论模型,采取双阈值小波去噪的有效方法,达到分离目标区域,保持良好边缘特性并获得良好去噪效果的目的,克服了传统的小波硬阈值过度"扼杀"图像信息的缺陷,优化了软阈值边缘特性的不足,同时解决了半软阈值算法复杂较难实现的根本问题。实验结果表明,本文方法原图像去噪后信噪比(SNR)可提高11%,熵值提高5.3%,均方根误差(RMSE)降低了6.9%,能有效地消除图像背景噪声,在不失真的情况下获取较为平滑的气泡图像,并保持气泡边缘特性,提高了后续流动特征的提取精度。
According to three-dimensional （3D） characteristic parameters of gas-liquid bubbly flow and high precision measurement requirements, double threshold wavelet denoising method is proposed for such noise characteristics to achieve gas-liquid multiple bubbles image denoising. Based on the theoretical models of hard threshold and soft threshold, we use double-threshold wavelet denoising method to divide target area effectively,maintain better edge characteristics and achieve a better result. The method can solve the problems that the hard-threshold wavelet denoising excessively strangles the real original information, the bubble edge characteristics cannot be optimized using soft-threshold effectively, and Semi-soft threshold algorithm is too complex to use in the practical applications. The experiment results show that the signal-to-noise ratio （SNR） of image aker denoising can be increased by 11 %, and the entropy is increased by 5.3 %. Compared with the general wavelet threshold denoising algorithm, root mean square error （RMSE） is reduced by 6.9%. The method can eliminate background noise effectively,smooth the images without image distortion, and maintain the edge feature of bubbles simultaneously. It improves the subsequent extraction accuracy of flow characteristic effectively.
出处
《光电子．激光》
EI
CAS
CSCD
北大核心
2016年第2期217-223,共7页
Journal of Optoelectronics·Laser
基金
国家自然科学基金(60902084
61372143)
天津市自然科学基金(12JCQNJC02200)资助项目
关键词
气液两相流
多气泡
双阈值小波去噪
高速摄影
gas-liquid bubbly flow
multiple bubbles
double-threshold wavelet denoising
high-speedphotography
