Particle image velocimetry from multispectral data

Since the adoption of digital video cameras and cross-correlation methods for particle image velocimetry (PIV), the use of color images has largely been abandoned. Recently, however, with the re-emergence of color-based stereo and volumetric techniques, color imaging for PIV has again become relevant. In this work we explore the potential advantages of color PIV processing by developing and proposing several methods for handling multi color images. The first method uses cross-correlation of every color channel independently to build a color vector cross-correlation plane which can be searched for one or more peaks corresponding to either the average displacement of several flow components using a color ensemble operation, or the individual motion of colored particles, each type with a different behavior. In the second case, linear unmixing is used on the correlation plane to separate out each known particle type as captured by the different color channels. The second method introduces the use of quaternions to encode the color data, and the cross-correlation is carried out simultaneously on all colors. The resulting correlation plane can either be searched for a single peak corresponding to the mean flow, or multiple peaks can be used with velocity phase separation to determine which velocity corresponds to which particle type. Each of these methods was tested using synthetic images simulating the color recording of noisy particle fields both with and without the use of a Bayer filter and demosaicing operation. It was determined that for single phase flow, both color methods decreased random errors by approximately a factor of 2 due to the noise signal being uncorrelated between color channels, while maintaining similar bias errors as compared to traditional monochrome PIV processing. In multi-component flows, the color vector correlation technique was able to successfully resolve displacements of two separate flow components with errors similar to traditional grayscale PIV processing of a single phase. It should be noted that traditional PIV processing is bound to fail entirely under such processing conditions. In contrast, the quaternion methods, frequently failed to properly identify the correct velocity and phase and showed significant cross-talk in the measurements between particle types. Finally, the color vector method was applied to experimental color images of a microchannel designed for contactless dielectrophoresis particle separation, and good results were obtained for both instantaneous and ensemble PIV processing. However, in both the synthetic color images that were generated using a Bayer filter and the experimental data, a significant peak locking effect with a period of two pixels was observed. In order to mitigate this detrimental effect it is suggested that improved image interpolation algorithms tuned for use in PIV are applied on the color images before processing, or that cameras that do not require a demosaic algorithm are used for PIV