Quality Improving Method for Schlieren Visualization Using Wavelet Analysis
Schlieren photography is a main optical flow visualization technology and is widely used. One problem existing in Schlieren visualization is the inevitable noises in result images: the background noise caused by, such as, uneven illuminance, and the random noise, such as CCD noise, etc. Image processing methods, especially those based on wavelet analysis, can handle these problems in a cost-effective way. A Schlieren image is decomposed through wavelet transform into an approximation, which is the component of useless background noise, and details, some of which represent information of the flow being examined and are called useful details, while the others are components of random noise. The useful details are weighted and then reconstructed into a new image which has a better view of the flow. It is shown by experiments that the visualization quality of a Schlieren image can be effectively improved through the processing described.
Schlieren photography flow visualization image de-noise wavelet analysis.
Zhang Mingzhao Wang Boxiong Luo Xiuzhi Ma Ling Zhu Xiaohua Ji Lingli
State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision In Equipment Research Institute of the Second Artillery, Beijing 100085, China
国际会议
北京
英文
2007-08-05（万方平台首次上网日期，不代表论文的发表时间）