From pixels to voxels: tracking volume elements in sequences of 3D digital images

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Abstract
We present an image analysis technique for examining the fine scale (Kolmogorov scale) variations of the mixing process in a turbulent flow. The objective is to trace the interaction of two flows by identifying their motions in a sequence of 3-D images obtained with a system based on a high-speed solid state camera. After briefly describing the imaging process and the particularities related to the capture of quasi-continuous 3-D image sequences, we focus on theoretical and implementational issues associated with feature tracking in 3-D image sequences. We present the extension of least squares matching from pixels, associated with 2- D images, to voxels, associated with 3-D images. The use of additional constraints of radiometric and/or geometric nature strengthens the matching solution. In addition, the large amount of data associated with 3-D image sequences in general, and the high and multidirectional velocities involved in this application in particular, make the division of an efficient matching strategy quite important.

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