Chien-Hung Lu

Phase retrieval using nonlinear diversity

We extend the Gerchberg-Saxton algorithm to phase retrieval in a nonlinear system. Using a tunable photorefractive crystal, we experimentally demonstrate the noninterferometric technique by reconstructing an unknown phase object from optical intensity measurements taken at different nonlinear strengths.

Quantitative Phase Imaging using Quantum Light

We experimentally demonstrate quantitative phase imaging using entangled photons. By using transport-of-intensity methods, we show that phase retrieval from quantum illumination is more sensitive and less noisy than that of classical light.

Enhanced phase retrieval using nonlinear dynamics

Historically, phase retrieval algorithms have relied on linear propagation between two different amplitude (intensity) measurements. While generally successful, these algorithms have many issues, including susceptibility to noise, local minima, and indeterminate initial and final conditions. Here, we show that nonlinear propagation overcomes these issues, as intensity-induced changes to the index of refraction create additional constraints on the phase. More specifically, phase-matching conditions (conservation of wave energy and momentum) induce an object-dependent resonance between the measured amplitudes and the unknown phase. The result is a non-classical convergence profile in the reconstruction algorithm that contains a zero crossing, where the observable minimum in amplitude error and the unobservable minimum in phase error align at the same iteration number. We demonstrate this convergence experimentally in a photorefractive crystal, showing that there is a clear rule for stopping iterations. We find that the optimum phase retrieval occurs for a nonlinear strength that gives minimal correlation between the linear and nonlinear output amplitudes, i.e. a condition that maximizes the information diversity between linear and nonlinear propagation. The corresponding algorithm greatly improves the conventional Gerchberg-Saxton result and holds much potential for enhancing other methods of diffractive imaging.

Flow-Scanning Microfluidic Imaging

The advantages of microfluidics for fast analysis of microscopic suspensions have led to the commercial development of flow cytometers. In this chapter, we propose new micro‐ scopy methods that combine controlled motion of micro-organisms in a laminar micro‐ fluidic flow, optics, and computation. We propose three new imaging modalities. We first introduce a flow-based version of structured illumination microscopy, where the necessa‐ ry phase shifts are no longer obtained by controlled displacement of the illumination pat‐ tern but by flowing the sample itself. Then, we propose a three-dimensional (3D) deconvolution microscopy method with a microfluidic device for continuous acquisition of gradually defocused images. Finally, we introduce a microfluidic device for phasespace image acquisition, and computational methods for the reconstruction of either phase of intensity, in 3D. The imaging modalities we introduce all retain the benefits of fluid systems for noninvasive bioimaging. The proposed devices can easily be integrated on existing microscopes as a modified microscope slide, or on flow cytometers, and aquatic imagers with minor adjustments. Alternative on-chip implementations are also possible, with lens-free devices, and near-field optical and microfluidic elements directly assembled on the surface of a CCD (Charge-Coupled Device) or CMOS (Complementary metal–oxide–semiconductor) chip.

Designer Illumination for Microscopy

We demonstrate improved imaging by shaping the illumination to match the object. The nonlinear feedback can surpass trade-offs in linear imaging, e.g. resolution vs. contrast, and lays the foundation for more general designer illumination.

Quantitative Phase Imaging using Entangled Photon Pairs

We experimentally demonstrate phase imaging using entangled photons and transport-of-intensity methods. We show that the reconstruction of an unknown phase object from quantum light is more sensitive and less noisy than that of classical illumination.

Microfluidic Structured Illumination Microscope

We apply the principle of structured illumination to microfluidic microscopy. Sample flow across the illumination pattern automatically gives the necessary phase shifts. We experimentally demonstrate the technique by reconstructing a superresolution image of yeast cells.

Phase Retrieval through Nonlinear Media

We extend the Gerchberg-Saxton algorithm to the phase retrieval through nonlinear media. We experimentally verify the technique by reconstructing a phase distribution from intensity measurements in two image planes with different positions.