Abstract
This paper explores several methods for increasing the efficiencyand accuracy of particle image velocimetry (PIV) data analysis. The time todirectly compute the correlation function to determine the displacement in PIVinterrogation windows is reduced using two techniques. First, a scheme thatcalculates the correlation for 16 pixels in parallel is implemented. A furtherincrease in efficiency results from using a truncated multiplication schemethat calculates 82% of the answer while reducing the work by 84%. Second,advantage is taken of the common practice of overlapping adjacentinterrogation windows by not recorrelating the portion of the new window thatoverlaps the old. For the commonly used 50% overlap, the speed of vectorcalculation can theoretically be increased 300%. In practice, the improvementdepends on the implementation of the method. The most efficient algorithmdoubles the processing speed at 50% overlap.Accuracy is increased using three methods. First, a technique for enhancingPIV images to increase the contrast between the particles and the backgroundis presented. This method is particularly useful when experimental exigenciesresult in low contrast images. Second, a method is presented for resolving thevelocity in areas of high velocity gradient where the correlation map containsmultiple peaks. Third, equalizing the histogram of sub-pixel adjustmentsshould eliminate peak locking. Sample data show a `decrease' in error of 15%.
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