Improving Holographic Search Algorithms using Sorted Pixel Selection

TL;DR

This paper introduces Sorted Pixel Selection, a modification to holographic search algorithms that reduces mean square error by approximately 15-20%, improving hologram quality with minimal additional computational cost.

Contribution

The paper proposes a novel SPS method that replaces random pixel selection in HSAs, achieving consistent MSE reductions across various test cases.

Findings

MSE reductions of 14.7 - 19.2% across test images

SPS improves hologram quality with limited overhead

Consistent performance gains in diverse scenarios

Abstract

Traditional search algorithms for computer hologram generation such as Direct Search and Simulated Annealing offer some of the best hologram qualities at convergence when compared to rival approaches. Their slow generation times and high processing power requirements mean, however, that they see little use in performance critical applications. This paper presents the novel Sorted Pixel Selection (SPS) modification for Holographic Search Algorithms (HSAs) that offers Mean Square Error (MSE) reductions in the range of 14.7 - 19.2% for the test images used. SPS operates by substituting a weighted search selection procedure for traditional random pixel selection processes. While small, the improvements seen are observed consistently across a wide range of test cases and require limited overhead for implementation.