Image sharpening algorithms used for phase retrieval to reconstruct images in digital holography are computationally intensive, requiring iterative virtual wavefront propagation and hill-climbing algorithms to optimize sharpness criteria. Recently, it was shown that minimum-variance wavefront prediction can be integrated with digital holography and image sharpening to significantly reduce the large number of costly sharpening iterations normally required to achieve near-optimal wavefront estimation [J. Opt. Soc. Am. A 35, 923 (2018) [CrossRef] ]. This paper demonstrates further gains in computational efficiency with a new subspace sharpening method in conjunction with predictive dynamic digital holography for real-time applications. The method sharpens local regions of interest in an image plane by parallel independent wavefront estimation on reduced-dimension subspaces of the complex field in a pupil plane. Through wave-optics simulations, this paper shows that the new subspace method produces results comparable to those of conventional global and local sharpening, and that subspace wavefront estimation and sharpening coupled with wavefront prediction achieve orders-of-magnitude increases in processing speed.

中文翻译：

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使用图像锐化和预测性动态数字全息术进行子空间波前估计。

用于相位检索以重建数字全息术中的图像的图像锐化算法的计算量很大，需要迭代虚拟波前传播和爬山算法来优化锐度标准。最近，显示出最小方差波阵面预测可以与数字全息术和图像锐化集成在一起，以显着减少通常为实现近乎最佳的波阵面估计所需的大量代价高昂的锐化迭代[J．选择。Soc。上午。甲35，923（2018）[交叉引用] ]。本文演示了一种新的子空间锐化方法以及预测性动态数字全息技术在实时应用中的计算效率进一步提高。该方法通过对光瞳平面中复数场的降维子空间进行并行独立的波前估计来锐化图像平面中的感兴趣局部区域。通过波光学仿真，本文表明，新的子空间方法产生的结果与常规的全局和局部锐化效果相当，并且子空间波阵面估计和锐化与波阵面预测相结合实现了处理速度的数量级提高。