采用同轴数字全息技术测量研究粒子场, 由于直透光、孪生像等因素的影响, 以及焦深(DOF)通常是粒子直径的数十倍以上, 造成了粒子轴向定位精度普遍较低。通过分析影响焦深大小的因素, 采用增大系统的数值孔径, 即减小记录距离可以明显降低焦深, 并提出一种用于粒子轴向定位的基于最大梯度的自动聚焦算法。自动聚焦算法中通过选择适当大小的对焦窗口将再现粒子包含在内, 对粒子边缘识别区域的任意可能的梯度方向都求出它的梯度, 利用比较后得到最大的梯度, 作为自动聚焦判别数据。同时, 考虑到算法的精确度和稳定性, 引入了阈值参数。经仿真和实验表明, 该算法具有较好的单峰性和稳定性, 可减小焦深对粒子轴向定位精度的影响。

The particle fields is generally measured by digital in-line holographic technique. But the resolution of particle axial position is lower due to the impact of zero-order image, twin-image noise and the depth of focus(DOF). Generally, DOF is tens of times as many as particle diameter. The large DOF has been a vexing problem in extraction of particle position from digital in-line holograms. DOF is affected by some recording parameters, i.e. NA of recording system, size of CCD, recording distance and the wavelength. Resolution of particle axial position can be improved by reducing depth of focus and recording distance. In this paper, an auto-focusing algorithm based on the most gradient for accurate location of particle by selecting proper window in accordance with particle size is proposed. At present, there are a lot of auto-focusing algorithms based on gradient, which calculate the gradient value only in appointed fixed directions, but the real gradient direction may not be the appointed direction. In order to solve the problem, an auto-focusing algorithm based on the most gradient and threshold is proposed. The gradients in all possible directions are calculated, then compare all of the possible gradients, and choose the largest gradient as the result. At the same time, in order to improve the precision and stability of auto-focusing algorithm, another threshold parameter is introduced. Through simulations and experiments, the algorithm has the characteristics such as strong single peak feature and good stability, which could decrease the impact of DOF to resolution of particle axial position.