Structured illumination and image enhancement of three-dimensional and moving objects at a distance via incoherent Fourier ptychography.

We experimentally apply incoherent Fourier ptychography to enhance the resolution of recorded images by projecting known, uncorrelated, random patterns at high speed onto 3D moving and distant objects. We find that the resolution enhancement factor can be greater than 2, depending on the projection and camera optics.

Multi-spectral SWIR lidar for imaging and spectral discrimination through partial obscurations.

We have developed a multi-spectral SWIR lidar system capable of measuring simultaneous spatial-spectral information for imaging and spectral discrimination through partial obscurations. We employ objects in the presence and absence of a series of obscurants to evaluate the capability of the system in classifying the objects of interest based on spectral and range information. We employ a principal component analysis-based algorithm in classifying the objects and quantifying the accuracy of detection under various obscured scenarios. The merits of multi-spectral lidar over hyperspectral imaging are highlighted for target identification in the presence of obscurants.

Separation of coherent and incoherent light using image plane vortex phase masks.

We consider the application of a modified optical vortex coronagraph as a transmissometer. We find, through theory and simulation, that the rejection of scattered light benefits from increasing the charge number of the vortex masks in the image plane, and that a combination of a vortex mask and binary pinhole can outperform the pinhole alone.

Spatial-spectral correlations of broadband speckle in around-the-corner imaging conditions.

Correlations of broadband speckle have important implications for passive, non-line-of-sight imaging. We examine the spectral and spatial correlations of broadband, around-the-corner speckle and reveal a set of equations that locate the spatial maximum of the paraxial spatial-spectral correlation function. We confirm the validity of the spatial-spectral correlation framework through experiment, theory and simulation.

Machine learning-aided classification of beams carrying orbital angular momentum propagated in highly turbid water: publisher's note.

This publisher's note corrects the name of an author of J. Opt. Soc. Am. A37, 1662 (2020)JOAOD60740-323210.1364/JOSAA.401153.

Transport-based pattern recognition versus deep neural networks in underwater OAM communications.

Comparisons between machine learning and optimal transport-based approaches in classifying images are made in underwater orbital angular momentum (OAM) communications. A model is derived that justifies optimal transport for use in attenuated water environments. OAM pattern demultiplexing is performed using optimal transport and deep neural networks and compared to each other. Additionally, some of the complications introduced by signal attenuation are highlighted. The Radon cumulative distribution transform (R-CDT) is applied to OAM patterns to transform them to a linear subspace. The original OAM images and the R-CDT transformed patterns are used in several classification algorithms, and results are compared. The selected classification algorithms are the nearest subspace algorithm, a shallow convolutional neural network (CNN), and a deep neural network. It is shown that the R-CDT transformed images are more accurate than the original OAM images in pattern classification. Also, the nearest subspace algorithm performs better than the selected CNNs in OAM pattern classification in underwater environments.

Imaging around corners in the mid-infrared using speckle correlations.

Speckle correlation imaging offers the ability to see objects through diffusive materials and around corners. Imaging self-illuminating thermal objects in non-line-of-sight scenarios is of particular interest. Here, using bispectrum and phase retrieval methods, we demonstrate speckle correlation imaging of mid-infrared objects through diffusers and around corners at resolutions near the diffraction limit. The images agree well with those recorded by conventional cameras with line-of-sight to the same objects.

Half-ring point spread functions.

We applied point spread function engineering to design an optimized diffuser producing half-ring irradiance patterns satisfying two objectives: reduced peak irradiance in the focal plane, and high fidelity of the reconstructed image. Applications of these optical elements may include sensor protection or reversible diffusers. Experimental and numerical techniques were used to demonstrate three orders of magnitude of suppression of the peak irradiance. Finally, we found a general power-law trend between the Strehl ratio and the light suppression factor.

Intensity-enhanced deep network wavefront reconstruction in Shack-Hartmann sensors.

The Shack-Hartmann wavefront sensor (SH-WFS) is known to produce incorrect measurements of the wavefront gradient in the presence of non-uniform illumination. Moreover, the most common least-squares phase reconstructors cannot accurately reconstruct the wavefront in the presence of branch points. We therefore developed the intensity/slopes network (ISNet), a deep convolutional-neural-network-based reconstructor that uses both the wavefront gradient information and the intensity of the SH-WFS's subapertures to provide better wavefront reconstruction. We trained the network on simulated data with multiple levels of turbulence and compared the performance of our reconstructor to several other reconstruction techniques. ISNet produced the lowest wavefront error of the reconstructors we evaluated and operated at a speed suitable for real-time applications, enabling the use of the SH-WFS in stronger turbulence than was previously possible.

Designing laser beams carrying OAM for a high-performance underwater communication system.

We present a design methodology for creating a distinct laser beam set suitable for detection by using only the recorded intensity pattern. We consider four coherent Laguerre-Gaussian beams carrying orbital angular momentum (OAM) to form the basis for optical communication. The complex electric fields of the beams are superimposed to create 16 dissimilar intensity patterns. The presented beam set design method considers the beam generation hardware limitations and aims to minimize the correlation among the messages and maximize their intensity differences. After propagating the 16 messages through a water channel, we measured high correlation, intensity similarity, and R-squared values for the identical messages and low values for the different ones. Distinct clustering between the measurements for the matching messages and the rest allows us to set a threshold in the gap among the groupings and successfully classify the received images.

Machine learning-aided classification of beams carrying orbital angular momentum propagated in highly turbid water.

A set of laser beams carrying orbital angular momentum is designed with the objective of establishing an effective underwater communication link. Messages are constructed using unique Laguerre-Gauss beams, which can be combined to represent four bits of information. We report on the experimental results where the beams are transmitted through highly turbid water, reaching approximately 12 attenuation lengths. We measured the signal-to-noise ratio in each test scenario to provide characterization of the underwater environment. A convolutional neural network was developed to decode the received images with the objective of successfully classifying messages quickly. We demonstrate near-perfect classification in all scenarios, provided the training set includes some images taken under the same underwater conditions.

Singular value decomposition approach to coherent averaging in digital holography.

We present a new approach to coherent averaging in digital holography using singular value decomposition (SVD). Digital holography enables the extraction of phase information from intensity measurements. For this reason, SVD can be used to statistically determine the orthogonal vectors that align the complex-valued measurements from multiple frames and group common modes accounting for constant phase shift terms. The SVD approach enables the separation of multiple signals, which can be applied to remove undesired artifacts such as scatter in retrieved images. The advantages of the SVD approach are demonstrated here in experiments through fog-degraded holograms with spatially incoherent and coherent scatter.

Computational optical sensing and imaging: introduction.

The OSA Topical Meeting on Computational Optical Sensing and Imaging (COSI) was held June 25-June 28, 2018 in Orlando, Florida, USA, as part of the Imaging and Applied Optics Congress. In this feature issue, we present several papers that cover the techniques, topics, and advancements in the field presented at the COSI meeting highlighting the integration of opto-electric measurement and computational processing.

Ptychographic imaging of incoherently illuminated extended objects using speckle correlations.

A scattering layer is usually considered an obstacle to imaging. However, using speckle correlation imaging techniques, the scattering layer effectively acts as a lens. To date, the speckle correlation imaging method has been limited to imaging sparse samples. Here, we demonstrate imaging of incoherently illuminated extended objects in transmission and around-the-corner geometries. We are able to image extended objects by constraining the illumination spot on the object and then scanning the object. A ptychography algorithm is used to reconstruct the extended object. This work demonstrates the applicability of ptychography to spatially incoherent light and enables a new method of imaging in spectral regions where there is limited choice in optics, such as the terahertz, extreme ultraviolet, and x-ray regions.

Optimized pupil-plane phase masks for high-contrast imaging.

A differential evolution algorithm (DEA) is shown to improve the design of phase-only pupil plane masks for imaging in the presence of a high-intensity point source. Strehl and suppression ratio metrics for various phase basis functions were experimentally and numerically calculated. Experiments performed with a spatial light modulator demonstrated 100 times suppression of the peak intensity. The Strehl ratio was found to be higher for the DEA masks compared to the individual phase basis function.

Machine learning approach to OAM beam demultiplexing via convolutional neural networks.

Orbital angular momentum (OAM) beams allow for increased channel capacity in free-space optical communication. Conventionally, these OAM beams are multiplexed together at a transmitter and then propagated through the atmosphere to a receiver where, due to their orthogonality properties, they are demultiplexed. We propose a technique to demultiplex these OAM-carrying beams by capturing an image of the unique multiplexing intensity pattern and training a convolutional neural network (CNN) as a classifier. This CNN-based demultiplexing method allows for simplicity of operation as alignment is unnecessary, orthogonality constraints are loosened, and costly optical hardware is not required. We test our CNN-based technique against a traditional demultiplexing method, conjugate mode sorting, with various OAM mode sets and levels of simulated atmospheric turbulence in a laboratory setting. Furthermore, we examine our CNN-based technique with respect to added sensor noise, number of photon detections, number of pixels, unknown levels of turbulence, and training set size. Results show that the CNN-based demultiplexing method is able to demultiplex combinatorially multiplexed OAM modes from a fixed set with >99% accuracy for high levels of turbulence-well exceeding the conjugate mode demultiplexing method. We also show that this new method is robust to added sensor noise, number of photon detections, number of pixels, unknown levels of turbulence, and training set size.

Experimental observations of a laser suppression imaging system using pupil-plane phase elements.

To help diminish the undesirable effects of laser irradiation on an imaging sensor, a pupil-plane phase element was introduced to broaden the point spread function, thereby reducing the focused laser irradiance. A sharpened image was subsequently restored via Wiener deconvolution. Successful experimental demonstrations employing a spatial light modulator in the pupil plane are reported for the vortex, axicon, and cubic phase. Furthermore, to circumvent information loss owing to zero values in the modulation transfer function, we demonstrate how images with different phase elements, combined with a joint deconvolution operation, provide an improved image.

Laguerre-Gauss and Bessel-Gauss beams propagation through turbulence: analysis of channel efficiency.

As a means of increasing the channel capacity in free-space optical communication systems, two types of orbital angular momentum carrying beams, Bessel-Gauss and Laguerre-Gauss, are studied. In a series of numerical simulations, we show that Bessel-Gauss beams, pseudo-nondiffracting beams, outperform Laguerre-Gauss beams of various orders in channel efficiency and bit error rates.

Efficient multibeam large-angle nonmechanical laser beam steering from computer-generated holograms rendered on a liquid crystal spatial light modulator.

Multibeam large-angle beam steering is demonstrated in the visible spectral region by imprinting computer-generated holographic Fresnel zone plates on a liquid crystal spatial light modulator (SLM) configured as the first element of a telescope. The position and intensity of each beam are controlled independently. The laser beam is steered over a ±37° field of regard, with the power in the beam at 37° being greater than 50% of the on-axis power. The power delivered on axis for a single beam was 48% of the power incident on the SLM. The beam profile remained Gaussian over the full steering range, and the on-axis beam divergence is 2.1 mrad.

Weak-signal iterative holography.

An iterative holographic table-top experiment is presented, where a recorded hologram is used to re-illuminate the initial target. With this beam shaping setup, more light is directed to the target for each iteration until a convergence limit is met. We experimentally examine convergence properties of this iterative hologram reconstruction approach for weak object signals and compare with theory.