Intrinsic parameter-free calibration of FPP using a ray phase mapping model.

This Letter presents a ray phase mapping model (RPM) for fringe projection profilometry (FPP) that avoids calibrating intrinsic parameters. The novelty of the RPM, to the best of our knowledge, is the ability to characterize the imaging system with independent rays for each pixel, and to associate the rays with the projected phase in the illumination field for efficient 3D mapping, which avoids complex imaging-specific modeling about lens layout and distortion. Two loss functions are constructed to flexibly optimize camera ray parameters and mapping coefficients, respectively. As a universal approach, it has the potential to calibrate different types of FPP systems with high accuracy. Experiments on wide-angle lens FPP, telecentric lens FPP, and micro-electromechanical system (MEMS)-based FPP are carried out to verify the feasibility of the proposed method.

3D imaging through a highly heterogeneous double-composite random medium by common-path phase-shift digital holography.

A method is proposed for 3D imaging through a highly heterogeneous double-composite random medium made of a thick mildly inhomogeneous medium followed by a thin strongly scattering layer. To realize the immunity to the heterogeneous random medium, a system of common-path phase-shift digital holography is designed in such a manner that the wavefront distortion caused by the first inhomogeneous medium is canceled out by the common-path geometry, and the influence of the random phase introduced by the second scattering layer is removed by the intensity-based recording of the digital hologram on the thin scattering layer. The validity of the method was confirmed by experiments.

Optimization of the holographic wavefront sensor for open-loop adaptive optics under realistic turbulence. Part I: simulations.

The modal holographic wavefront sensor enables fast measurement of individual aberration modes without the need for time-consuming calculations. However, the measurement accuracy suffers greatly from intermodal crosstalk, caused when the wavefront contains more aberrations than the one to be measured. In this paper, we present sensor optimization to minimize this effect and show the improvement when using Karhunen-Lòeve instead of Zernike modes as the basis. Finally, we show in simulation that an open-loop adaptive optics system based on the optimized sensor can be used to correct the effect of realistic, dynamic atmospheric turbulence on a wavefront and increase its Strehl ratio significantly.

Single-pixel scatter-plate microscopy.

Based on the optical memory effect of scattered light, we developed a new single-pixel camera concept. The retrieved images contain both 3D and spectral information about the sample. A spatial light modulator (SLM) generates a random intensity modulation. The signal recorded by the single-pixel detector is cross correlated by the calculated point spread function (PSF) signals of the SLM to retrieve the image. In this publication, both simulations and experimental results are presented.

Scatter-plate microscopy with spatially coherent illumination and temporal scatter modulation.

Scatter-plate microscopy (SPM) is a lensless imaging technique for high-resolution imaging through scattering media. So far, the method was demonstrated for spatially incoherent illumination and static scattering media. In this publication, we demonstrate that these restrictions are not necessary. We realized imaging with spatially coherent and spatially incoherent illumination. We further demonstrate that SPM is still a valid imaging method for scatter-plates, which change their scattering behaviour (i.e. the phase-shift) at each position on the plate continuously but independently from other positions. Especially we realized imaging through rotating ground glass diffusers.

Lensless light-field imaging through diffuser encoding.

Microlens array-based light-field imaging has been one of the most commonly used and effective technologies to record high-dimensional optical signals for developing various potential high-performance applications in many fields. However, the use of a microlens array generally suffers from an intrinsic trade-off between the spatial and angular resolutions. In this paper, we concentrate on exploiting a diffuser to explore a novel modality for light-field imaging. We demonstrate that the diffuser can efficiently angularly couple incident light rays into a detected image without needing any lens. To characterize and analyse this phenomenon, we establish a diffuser-encoding light-field transmission model, in which four-dimensional light fields are mapped into two-dimensional images via a transmission matrix describing the light propagation through the diffuser. Correspondingly, a calibration strategy is designed to flexibly determine the transmission matrix, so that light rays can be computationally decoupled from a detected image with adjustable spatio-angular resolutions, which are unshackled from the resolution limitation of the sensor. The proof-of-concept approach indicates the possibility of using scattering media for lensless four-dimensional light-field recording and processing, not just for two- or three-dimensional imaging.

Single-shot structured-light-field three-dimensional imaging.

This Letter reports an approach to single-shot three-dimensional (3D) imaging that is combining structured illumination and light-field imaging. The sinusoidal distribution of the radiance in the structured-light field can be processed and transformed to compute the angular variance of the local radiance difference. The angular variance across the depth range exhibits a single-peak distribution trend that can be used to obtain the unambiguous depth. The phase computation that generally requires the acquisition of multi-frame phase-shifting images is no longer mandatory, thus enabling single-shot structured-light-field 3D imaging. The proposed approach was experimentally demonstrated through a dynamic scene.

Phase imaging with an untrained neural network.

Most of the neural networks proposed so far for computational imaging (CI) in optics employ a supervised training strategy, and thus need a large training set to optimize their weights and biases. Setting aside the requirements of environmental and system stability during many hours of data acquisition, in many practical applications, it is unlikely to be possible to obtain sufficient numbers of ground-truth images for training. Here, we propose to overcome this limitation by incorporating into a conventional deep neural network a complete physical model that represents the process of image formation. The most significant advantage of the resulting physics-enhanced deep neural network (PhysenNet) is that it can be used without training beforehand, thus eliminating the need for tens of thousands of labeled data. We take single-beam phase imaging as an example for demonstration. We experimentally show that one needs only to feed PhysenNet a single diffraction pattern of a phase object, and it can automatically optimize the network and eventually produce the object phase through the interplay between the neural network and the physical model. This opens up a new paradigm of neural network design, in which the concept of incorporating a physical model into a neural network can be generalized to solve many other CI problems.

Precise building deformation measurement using holographic multipoint replication.

For the active control of large-scale structures, especially high-rise buildings and bridges, fast and accurate measurement of local deformations is required. We present a highly accurate and fast vision-based measurement technique and, to the best of our knowledge, first experimental results for the control of an adaptive-structures prototype frame, equipped with hydraulic actuators. Deformations are detected at multiple discrete points, based on a photogrammetric approach with additional holographic spot replication. The replication leads to effective averaging of most error contributions, especially discretization and photon noise. Measurements over a distance of 11.4 m result in a measurement uncertainty of 0.0077 pixel (corresponding to 0.055 mm in object space).

Light-field depth estimation considering plenoptic imaging distortion.

Light-field imaging can simultaneously record spatio-angular information of light rays to carry out depth estimation via depth cues which reflect a coupling of the angular information and the scene depth. However, the unavoidable imaging distortion in a light-field imaging system has a side effect on the spatio-angular coordinate computation, leading to incorrectly estimated depth maps. Based on the previously established unfocused plenoptic metric model, this paper reports a study on the effect of the plenoptic imaging distortion on the light-field depth estimation. A method of light-field depth estimation considering the plenoptic imaging distortion is proposed. Besides, the accuracy analysis of the light-field depth estimation was performed by using standard components. Experimental results demonstrate that efficiently compensating the plenoptic imaging distortion results in a six-fold improvement in measuring accuracy and more consistency across the measuring depth range. Consequently, the proposed method is proved to be suitable for light-field depth estimation and three-dimensional measurement with high quality, enabling unfocused plenoptic cameras to be metrological tools in the potential application scenarios such as industry, biomedicine, entertainment, and many others.

Three-dimensional microscopic imaging through scattering media based on in-line phase-shift digital holography.

Microscopic three-dimensional imaging and phase quantification for objects hidden behind a scattering medium by using in-line phase-shift digital holography are proposed. A spatial resolution of 1.81 µm and highly accurate quantitative phase imaging are demonstrated for objects behind a scatter plate. Three-dimensional imaging was confirmed using objects with a depth difference of 1.32 mm. Further, imaging was performed using rat skin as a demonstration for imaging through a complex multilayer scattering medium, where a spatial resolution close to the theoretically predicted value was achieved by experiment.

Unfocused plenoptic metric modeling and calibration.

For unfocused plenoptic imaging systems, metric calibration is generally mandatory to achieve high-quality imaging and metrology. In this paper, we present an explicit derivation of an unfocused plenoptic metric model associating a measured light field in the object space with a recorded light field in the image space to conform physically to the imaging properties of unfocused plenoptic cameras. In addition, the impact of unfocused plenoptic imaging distortion on depth computation was experimentally explored, revealing that radial distortion parameters contain depth-dependent common factors, which were then modeled as depth distortions. Consequently, a complete unfocused plenoptic metric model was established by combining the explicit metric model with the imaging distortion model. A three-step unfocused plenoptic metric calibration strategy, in which the Levenberg-Marquardt algorithm is used for parameter optimization, is correspondingly proposed to determine 12 internal parameters for each microlens unit. Based on the proposed modeling and calibration, the depth measurement precision can be increased to 0.25 mm in a depth range of 300 mm, ensuring the potential applicability of consumer unfocused plenoptic cameras in high-accuracy three-dimensional measurement.

Image reconstruction and enhancement by deconvolution in scatter-plate microscopy.

We investigated the capabilities of deconvolution for image enhancement in scatter-plate microscopy. This lensless imaging technique enables the investigation of microstructures through scattering media by cross-correlating the scattered light intensity with a previously recorded point spread function (PSF) of the scattering medium. The autocorrelation function of the PSF appears as the transfer function of the imaging process. Deconvolution methods use the knowledge of this transfer function to enhance the image quality by reducing the blur and strengthening the contrast with the objective to achieve diffraction-limited resolution. We obtained significant image enhancement both with means of inverse filtering and by applying iterative deconvolution algorithms.

Accurate depth estimation in structured light fields.

Passive light field imaging generally uses depth cues that depend on the image structure to perform depth estimation, causing robustness and accuracy problems in complex scenes. In this study, the commonly used depth cues, defocus and correspondence, were analyzed by using phase encoding instead of the image structure. The defocus cue obtained by spatial variance is insensitive to the global spatial monotonicity of the phase-encoded field. In contrast, the correspondence cue is sensitive to the angular variance of the phase-encoded field, and the correspondence responses across the depth range have single-peak distributions. Based on this analysis, a novel active light field depth estimation method is proposed by directly using the correspondence cue in the structured light field to search for non-ambiguous depths, and thus no optimization is required. Furthermore, the angular variance can be weighted to reduce the depth estimation uncertainty according to the phase encoding information. The depth estimation of an experimental scene with rich colors demonstrated that the proposed method could distinguish different depth regions in each color segment more clearly, and was substantially improved in terms of phase consistency compared to the passive method, thus verifying its robustness and accuracy.

Extending the depth-of-field of imaging systems with a scattering diffuser.

Large depth of field (DOF) is a longstanding goal in optical imaging field. In this paper we presented a simple but efficient method to extend the DOF of a diffraction-limited imaging system using a thin scattering diffuser. The DOF characteristic of the imaging system with random phase modulation was analyzed based on the analytical model of ambiguity function as a polar display of the optical transfer function (OTF). The results of numerical simulation showed that more high-frequency components existed in the defocused OTF curve when the exit pupil of the imaging system exhibited a random phase modulation. It proved the important role of the scattering diffuser in extending the DOF of imaging systems. For the reconstruction, a stack of point spread functions (PSFs) corresponding to different axial locations within a measurement range were superimposed to construct the stacked PSF. Then the large DOF image was recovered from a speckle pattern by deconvolution. In this proof-of-concept, we experimentally demonstrated the single-shot imaging with larger DOF using a thin glass scattering diffuser in both a single-lens imaging system and a microscopic imaging system.

Feasibility study of digital holography for erosion measurements under extreme environmental conditions inside the International Thermonuclear Experimental Reactor tokamak [invited].

In the International Thermonuclear Experimental Reactor under construction in southern France, there will be a need for continuous measuring of the erosion at the wall, after the reactor starts operating. A two-wavelength interferometric technique based on digital holography is proposed for the erosion measurement. This technique has the ability to tackle the challenging environmental conditions within the reactor by a long-distance measurement, where a relay optic will be used for imaging the investigated surface on the detector. We will show that the shape measurements of objects located at a distance of more than 20 m from the measuring head can be carried out in a short time (100 µs) by the two-wavelength interferometric technique. A depth accuracy of ±10 µm is achieved.

Improving reconstruction of speckle correlation imaging by using a modified phase retrieval algorithm with the number of nonzero-pixels constraint.

Speckle correlation imaging (SCI) has been considered one of the most promising techniques for computational imaging through a scattering medium. However, the image quality is not always acceptable in conventional SCI, especially when a complex object is involved. In this work, a modified phase retrieval algorithm is introduced to significantly improve the imaging quality of SCI. In the proposed scheme, nonzero-pixel constraints, rather than the real and nonnegative constraints, are employed as the object domain constraints of the iterative algorithm in the image reconstruction process. Experimental results are presented to show the performance enhancement of this scheme, inclusive of less iterations, better image quality, and higher reliability, in comparison with the conventional SCI method.

Light-field-based absolute phase unwrapping.

Ambiguity caused by a wrapped phase is an intrinsic problem in fringe projection-based 3D shape measurement. Among traditional methods for avoiding phase ambiguity, spatial phase unwrapping is sensitive to sensor noise and depth discontinuity, and temporal phase unwrapping requires additional encoding information that leads to an increase of image sequence acquisition time or a reduction of fringe contrast. Here, to the best of our knowledge, we report a novel method of absolute phase unwrapping based on light field imaging. In a recorded light field under structured illumination, i.e., a structured light field, a wrapped phase-encoded field can be retrieved and resampled in diverse image planes associated with several possible fringe orders in a measurement volume. Then, by leveraging phase consistency constraint in the resampled wrapped phase-encoded field, correct fringe orders can be determined to unwrap the wrapped phase without any additional encoding information. Experimental results demonstrated that the proposed method was suitable for accurate and robust absolute phase unwrapping.

Optically addressed modulator for tunable spatial polarization control.

We present an optically addressed non-pixelated spatial light modulator. The system is based on reversible photoalignment of a LC cell using a red light sensitive novel azobenzene photoalignment layer. It is an electrode-free device that manipulates the liquid crystal orientation and consequently the polarization via light without artifacts caused by electrodes. The capability to miniaturize the spatial light modulator allows the integration into a microscope objective. This includes a miniaturized 200 channel optical addressing system based on a VCSEL array and hybrid refractive-diffractive beam shapers. As an application example, the utilization as a microscope objective integrated analog phase contrast modulator is shown.

Cascaded DBR plasmonic cavity lens for far-field subwavelength imaging at a visible wavelength.

We experimentally demonstrate a novel cascaded plasmonic superlens, which can directly image subwavelength objects with magnification in the far field at a wavelength of 640nm. The lens consists of two plasmonic slabs. One is a plasmonic cavity lens used for near-field coupling, and the other one is a planar plasmonic lens for phase compensation and thus, image magnification. To tune the performance wavelength to visible and to enhance the near-field transmission, distributed Bragg reflectors are integrated to the plasmonic cavity lens around the lens center, forming additional lateral cavities for surface waves. In this article, we first show numerical results about the working principle and the performance of the lens. Then, we demonstrate the imaging performance of a fabricated superlens experimentally. The fabricated superlens exhibits a lateral resolution down to 200 nm at the wavelength of 640 nm observed in the far field. Compared to our earlier design, shift invariance is achieved with the current approach. Our results could open a way for designing and fabricating novel miniaturized plasmonic superlenses in the future.