Evaluating autofocusing metrics for plankton holographic microscope image reconstruction

Abstract

Holographic reconstruction algorithms based on wave propagation typically require the object's Z-plane location. To automate reconstruction, a focus metric is required to iteratively determine the Z-plane location. The 1951 USAF resolution test chart is often used to evaluate holographic reconstruction and focus metric performance. However, plankton present a more difficult subject, as they are dense three-dimensional objects with lower contrast and greater gray-scale variance. In addition, we are using a direct inline red laser and image sensor without optics, operating below lasing threshold to avoid speckle, resulting in modest fringe production. These factors make autofocusing more difficult. In this paper we evaluate six focus methods tested on eight classes of plankton and microfiber (n = 64), measuring Z prediction accuracy and computation time. We show that focus method performance varies with class, suggesting that best performance can be achieved by selecting the focus metric based on the specimen class of interest.