Abstract
In video-based particle-image velocimetry (PIV) systems for fluid mechanics research, it is sometimes desirable to image seed particles to be smaller than a camera pixel. However, imaging to this size can lead to marginal image contrast such that significant numbers of erroneous velocity vectors can be computed, even for simple flow fields. A variety of image-enhancement techniques suitable for a low-cost PIV system that uses video cameras are examined and tested on three representative flows. Techniques such as linear contrast enhancement and histogram hyperbolization are shown to have good potential for improving the image contrast and hence the accuracy of the data-reduction process with only a 15% increase in the computational time. Some other schemes that were examined appear to be of little practical value in PIV applications. An automated shifting algorithm based on mass conservation is shown to be useful for displacing the second interrogation region in the direction of flow, which minimizes the number of uncorrelated particle images that contribute noise to the data-reduction process.
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