Subsampled Phase Retrieval for On-chip Lensless Holographic Video

TL;DR

This paper introduces a subsampled phase retrieval algorithm that significantly increases the frame rate of on-chip holographic video by reducing pixel measurements, enabling high-resolution biological monitoring at higher temporal resolutions.

Contribution

The paper presents a novel subsampled phase retrieval method that reduces measurement requirements by over tenfold, improving holographic video frame rates without sacrificing image quality.

Findings

Achieved a 5.5x increase in sensor frame rate in experiments.

Maintained high-quality reconstructions with significantly fewer measurements.

Demonstrated real-time monitoring of microorganisms in vivo.

Abstract

On-chip holographic video is a convenient way to monitor biological samples simultaneously at high spatial resolution and over a wide field-of-view. However, due to the limited readout rate of digital detector arrays, one often faces a tradeoff between the per-frame pixel count and frame rate of the captured video. In this report, we propose a subsampled phase retrieval (SPR) algorithm to overcome the spatial-temporal trade-off in holographic video. Compared to traditional phase retrieval approaches, our SPR algorithm uses over an order of magnitude less pixel measurements while maintaining suitable reconstruction quality. We use an on-chip holographic video setup with pixel sub-sampling to experimentally demonstrate a factor of 5.5 increase in sensor frame rate while monitoring the in vivo movement of Peranema microorganisms.