Improving the spatial dynamic range of digital inline particle holography

Abstract

Digital inline holography has been proven to provide three-dimensional droplet position, size, and velocity distributions with a single camera. These data are crucial for understanding multiphase flows. In this work, we examine the performance of this diagnostic in the limit of very small particles, on the order of a pixel in diameter and smaller, and propose a postprocessing method to improve them: Lanczos interpolation. The Lanczos interpolation kernel is the digital implementation of the Whittaker sinc filter and strikes a compromise between maintaining the spatial frequency ceiling of the original digital image and computational cost of the interpolation. Without Lanczos interpolation, or supersampling, the ultimate detectable particle size floor is on the order of four pixel widths. We show in this work that this limit can be reduced by 50% or more with supersampling, depending upon the desired diameter accuracy, and examine the effect of supersampling on the resulting accuracy of the extracted size and position of spherical particles. Extending this resolution limit increases the overall detection efficiency of the diagnostic. Since this increases the spatial dynamic range of the diagnostic, it can also allow a larger field of view to be captured with the same particle size floor.