Abstract
In this paper the wavelet-based image compression technique is applied to PIV processing for reducing noise in images and reducing the physical storage. To determine the effect of the choice of the wavelet bases, the standard PIV images are compressed by some known wavelet families, Daubechies, Coifman, and baylkin families. It was found that high order wavelet bases provides good compression performance for compressing PIV Images, because they have good frequency localization that in turn increases the energy compaction. The reconstructed PIV image with lower compression ratio may emphasize particle edges at a relatively high spatial resolution, and the reconstructed PIV image with higher compression ratio may display the large-scale motion of particles and may deduce noisy. In this study, higher compression ratio, from 25% to 6.25%, can be realized without losing significant flow information in PIV processing. It can say that the wavelet image compression technique is effective in PIV system.
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