One of the major technological difficulties in implementing digital particle image velocimetry (PIV) is associated with acquiring, processing and storing large volumes of image data form high resolution CCD camera(s). Current CCD camera technology provides both very high resolutions and high frame rates typically producing tens of megabytes of data per second. With the need for simultaneous data form two or more image sources the problems of data transmission, processing and storage become extreme. Significant increases in transfer, processing and storage can be achieved by compressing images by removing components of the image that are redundant or of low significance. This paper presents an approach to PIV image compression and methods of processing encoded data. The effect of varying levels of compression on data transfer and processing rates as well as measurements precision is considered and illustrated with results from both real and synthetic image data.
Holography is a method by which information of a 3D object space can be recorded. Used to record the position of neutrally buoyant tracers in a flow at two or more briefly separated instants it provides the means to record complex 3D velocity distributions. The magnitude of data contained in a holographic recording and the complexity of extracting flow displacement values from within a random distribution of holographically recorded seed particles makes automated analysis desirable. The analysis system described here is based on 3D correlation processing and provides an accurate and reliable means of detecting and measuring the local 3D displacements from a background of randomly positioned particles.
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