Estimation of In Situ 3-D Particle Distributions From a Stereo Laser Imaging Profiler

Abstract

In this paper, an image processing system for estimating 3-D particle distributions from stereo light scatter images is described. The system incorporates measured, three-component velocity data to mitigate particle blur associated with instrument motion. An iterative background estimation algorithm yields a local threshold operator that dramatically reduces bias in particle counts over the full image field. Algorithms are tested on simulated particle distributions and data from an open-ocean profile collected near the Santa Barbara Channel Islands, CA. They yield over a 50% reduction in root-mean-squared error in particle size estimates, and a 30% reduction in the magnitude of the motion blur point spread function. In situ particle distributions are estimated and compared to several models. It is demonstrated that quantitative, 3-D particle distributions can be accurately estimated from these data for particles with diameter larger than 4 pixels (0.8 mm).