Linear time algorithm for phase sensitive holography

TL;DR

This paper introduces a novel algorithm that reduces the computational complexity of phase-sensitive holography from quadratic to linear time, enabling faster high-quality hologram generation with guaranteed convergence.

Contribution

The paper presents a new technique reformulating the error metric to achieve linear time complexity in hologram computation, significantly improving speed over traditional methods.

Findings

Achieved approximately 50,000x speed-up on 1024x1024 images.

Guaranteed convergence to a global minimum in linear time.

Reduced computational complexity from O(N_x^2 N_y^2) to O(N_x N_y).

Abstract

Holographic search algorithms such as direct search and simulated annealing allow high-quality holograms to be generated at the expense of long execution times. This is due to single iteration computational costs of $O(N_x N_y)$ and number of required iterations of order $O(N_x N_y)$, where $N_x$ and $N_y$ are the image dimensions. This gives a combined performance of order $O(N_x^2 N_y^2)$. In this paper we use a novel technique to reduce the iteration cost down to $O(1)$ for phase-sensitive computer generated holograms giving a final algorithmic performance of $O(N_x N_y)$. We do this by reformulating the mean-squared error metric to allow it to be calculated from the diffraction field rather than requiring a forward transform step. For a $1024\times 1024$ pixel test images this gave us a $\approx 50,000\times$ speed-up when compared with traditional direct search with little additional complexity. When applied to phase-modulating or amplitude-modulating devices the proposed algorithm converges on a global minimum mean squared error in $O(N_x N_y)$ time. By comparison, most extant algorithms do not guarantee a global minimum is obtained and those that do have a computational complexity of at least $O(N_x^2 N_y^2)$ with the naive algorithm being $O((N_xN_y)!)$.