Image Processing Techniques for Shock Wave Detection and Tracking in High Speed Schlieren and Shadowgraph Systems

Schlieren and shadowgraph photography has been widely used to offer insight into the flow field in aerospace engineering due to their ease of application. The high-speed schlieren and shadowgraph techniques are typically applied to investigation of unsteady shock wave structure including shock reflection patterns and shock wave/boundary layer interactions, etc. Generally, qualitative analysis is performed based on the schlieren and shadowgraph image sequences. To process and analyze the large data set of the high-speed schlieren and shadowgraph images quantitatively, especially for the shock wave detection and tracking, a software was developed based on MATLAB GUI and its image processing toolbox. In this study, the image processing techniques exploited in the software, such as background subtraction, filter, threshold, edge detection, and shock tracking are presented. A case study on the phenomena of shock wave reflection from a solid surface was conducted. The results show that the proper filter method and the background image subtraction can effectively eliminate the image noises in frequency domain, which makes it easier to analyze the flow structure. Moreover, the instantaneous locations of shock waves are detected accurately, and the shock wave propagation speed calculated using the developed software are consistent with those of previous studies.