Editor-in-Chief Adam Wax announces the retirement of longtime Senior Editors Rajpal Sirohi and Patti Gillespie.

In the digital era, sharing pictures on social media has become a common privacy issue. To prevent private images from being eavesdropped on and destroyed, developing secure and efficient image steganography, image cryptography, and image authentication has been difficult. Deep learning provides a solution for digital image security. First, we make an overall conclusion on deep learning applications in image steganography to generate five aspects: the cover image, stego-image, embedding change probabilities, coverless steganography, and steganalysis. Second, we also combine and compare deep learning methods used in six aspects: image cryptography from image compression, image resolution improvement, image object detection and classification, key generation, end-to-end image encryption, and image cryptoanalysis. Third, we collect deep learning methods in image authentication from five perspectives: image forgery detection, watermarked image generation, image watermark extraction and detection, image watermarking attack, and image watermark removal. Finally, we summarize future research directions of deep learning utilization in image steganography, image cryptography, and image authentication.

It is always a challenging task to detect a small target with low signal-to-noise ratio under complex background in infrared images. To address this problem, an effective algorithm based on background subtraction is proposed. First, we add the gradient feature into the kernel regression model to acquire an edge-preserving background estimation. The smoothing matrix of the kernel function is reestablished by a rotation angle and an elongation scale. Further, a multiscale first-order directional derivative filter is presented to calculate these factors adaptively. Second, to segment the real target from the subtracted image, we model the imaging process of the small target using the point spread function of the optical system. According to the analysis of the imaging size and the energy distribution of target, an energy concentration criterion is constructed and used for target extraction. Finally, comparison of experimental results demonstrates that the proposed algorithm achieves robust performances on background suppression and extracts the target accurately with a high detection probability and low false alarm rate.

Infrared image and visible image can provide the thermal radiation and optical information of objects respectively. Hence, fusing their complementary information for a scene is essential for both human vision and machine perception. The adaptability of image fusion by multiscale transform (MST) is weak because of the fixed fusion rule. Meanwhile, the image fusion algorithm by supervised learning is hard to realize for lack of large labeled data. Therefore, we propose a unified framework for infrared and visible-image fusion via MST and feature learning. The reasonable fusion rule is designed by learning the attention response via training a novel attention architecture built-in the attention-guided generative adversarial network, which does not need the fused result as the ground truth. The experiment results demonstrate the validity of feature learning and the superiority of the proposed algorithm against other state-of-the-art methods in image fusion task. And the proposed method is one of the effective ways to promote the development of deep learning in the field of insufficient labeled data.

Autostereoscopic three-dimensional (3D) display has attracted considerable attention in recent years. To achieve high-quality 3D display with the lenticular-lens array, the accurate 3D display parameters of the lenticular-lens array need to be measured, including lines per inch (LPI) and slanted angle. Traditional methods generally measured the 3D display parameters by manually observing white-black characteristic 3D images synthesized based on the LPI and slanted angle. However, these methods have problems with time-consuming, inaccurate estimations, or limited applications. To address these problems, a method based on deep reinforcement learning (DRL) is proposed, which can automatically measure the 3D display parameters of the lenticular-lens array. In our method, the white-black characteristic 3D image is initialized based on the coarse LPI and slanted angle. Then the 3D image is captured by a camera from a 3D display device and input into a convolutional neural network (CNN) based on DRL. Finally, the CNN is used to optimize the LPI and slanted angle, and the accurate 3D display parameters can be measured. Experimental results show that our method can efficiently measure accurate 3D display parameters with roughly initial parameter values. We hope our study will make a valuable contribution to the field of autostereoscopic 3D display.

We propose an autostereoscopic display using a parallax barrier with an eye-tracking system to expand the viewing zone in all directions in both portrait and landscape modes. High-quality 3D images can be observed even if the viewer moves from the optimum viewing position. According to the viewing position, we divide a screen into multiple areas and control the optimal binocular image positions of each divided area to expand the viewing zone in the depth direction. The same eye-tracking algorithm can be applied to barriers in the portrait and landscape modes. To verify the effectiveness of the proposed system, we measured the crosstalk ratio of prototypes according to the viewing position.

Thermal aberration of a projection lens is caused by lens heating and leads to degradation of image quality. Two tasks have been undertaken in this article: first, analysis of the impact of single aberration on imaging quality, and second, use of machine learning to calculate the combination of Zernike aberration coefficients to reduce the influence of aberration on the process window. The impact of aberration on deep ultraviolet (DUV) lithography imaging has been analyzed separately for 16 Zernike terms. The influence of single Zernike coefficient on depth of focus, mask error enhancement factor, and image log slope is comprehensively analyzed by source mask optimization. However, more than one Zernike term is present in the aberration of a real DUV optics. A fully connected neural network (FCNN) model based on machine learning is widely used in the screening of multivariate experiments and can solve the problem of the large number of input variables and the random values of the input data. Its network structure is simple to debug, with fast screening speed and high precision. To make reasonable budget for aberration, an FCNN model is used to find some combinations of Zernike coefficients for different lithographic performance indicators. This implies that the FCNN model has the ability to select a better Zernike combination while each individual Zernike term value falls in the range of −30 to 30  mλ, which plays a guiding role in DUV optics design.

High-resolution spectral imaging of objects on ocean surfaces is difficult, because the position of these objects and the water waves on the ocean surface, as well as the illumination, vary over time. We propose a method for the reconstruction of spectral images of ocean surfaces based on the response of a standard RGB (sRGB) imaging system and a group of ocean spectrum samples. First, we measured the spectral reflectance of a typical ocean surface in the visible band using a standard spectroradiometer. Using transformations in the hue, saturation, and brightness dimensions, we then expanded these measurements to form a reference group of spectral reflectance samples along with their corresponding sRGB values. Following this, we established a method for reconstructing the spectral image cube of an ocean surface from a single sRGB image using a spectrum dictionary and RGB value matching. Our technique thus eliminates the problem of conversion from a three-dimensional RGB space to a multidimensional spectral space faced by conventional spectral reconstruction methods. In our experiments, we captured a series of sRGB standard images of a typical ocean surface using a standard digital color camera, and then reconstructed the spectral image cube from 400 to 700 nm using a 5-nm interval. Based on assessment of the quality of the reconstructed spectral images, our technique demonstrates desirable performance with respect to spectral distribution and spatial resolution.

Images recorded by coherent imaging systems, including laser-based photography, digital holography (DH), and digital holographic microscopy (DHM), are severely distorted by speckle noise. We present a single-shot image processing method to reduce the speckle noise, coined hybrid median–mean filter (HM2F), which is based on the average of conventional median-filtered images with different kernel sizes. The synergic combination of the median filter and mean approach provides a denoised image with reduced speckle contrast while the spatial resolution is kept at up to 97% of the original value. The HM2F method is compared with the conventional median filter approach, the 3D block matching filter, the nonlocal means filter, the 2D windowed Fourier transform filter, and the Wiener filter using different speckle-distorted images to benchmark its performance. Based on the experimental results and the simplicity of the technique, HM2F is proposed as an effective denoising tool for reducing the speckle noise in laser-based photography, DH, and DHM.

We proposed a fast three-dimensional (3D) structured illumination photoacoustic microscopy (PAM). In the conventional PAM systems, the optical and acoustical beams need mechanical scanning to cover the whole area of interest for imaging imposing constraint on imaging speed. Using sinusoidal fringe illumination resulted in interference from a pair of tilted plane waves of different directions; capturing the resultant acoustic signal via a transducer array helped to improve lateral resolution and speed of the system while not degrading the depth-of-field (DOF). The sinusoidal structured illumination helps in more complete capture of spatial frequency components, which could be approved through a mathematical model of the system. Capturing more frequency components, in turn, results in improved frequency bandwidth and thus lateral resolution of the system. Simulation results show 5.4 dB improvements in image quality, based on the peak signal-to-noise ratio compared with a conventional structure.

We present a practical machine learning (ML) method for serving accessible nonlinear functions, which tackles a regression problem with tremendous parameters. By solving the modified Lugiato–Lefever equation, datasets for emulating the silicon-on-insulator platform and generating the on-chip optical frequency comb (OFC) are gathered. Furthermore, a feed-forward network-based ML model is used to train the datasets, and the prediction of the related parameters is implemented synchronously. Numerical results show that the model combining the finite element method with the ML technique is capable of predicting the properties of on-chip frequency combs for the first time, as far as we know, paving the way for analyzing OFCs based on integrated silicon photonics.

Deformable mirrors (DMs) have wide applications ranging from astronomical imaging to laser communications and vision science. However, they often require bulky multi-channel cables for delivering high power to their drive actuators. A low-powered DM, which is driven in a contactless fashion, could provide a possible alternative to this problem. We present a photomagnetically actuated deformable mirror (PMADM) concept, which is actuated in a contactless fashion by a permanent magnet and low-power laser heating source. We present the laboratory demonstration of prototype optical surface quality, magnetic control of focus, and COMSOL simulations of its precise photocontrol. The PMADM prototype is made of a magnetic composite (polydimethylsiloxane + ferromagnetic CrO₂) and an optical-quality substrate layer and is 30.48  mm  ×  30.48  mm  ×  175  μm in dimension with an optical pupil diameter of 8 mm. It deforms to 5.76  μm when subjected to a 0.12-T magnetic flux density and relaxes to 3.76  μm when illuminated by a 50-mW laser. A maximum stroke of 8.78  μm before failure is also estimated considering a 3  ×   safety factor. Our work also includes simulation of astigmatism generation with the PMADM, a first step in demonstrating control of higher order modes. A fully developed PMADM may have potential application for wavefront corrections in vacuum and space environments.

In planar optics machining, surface flatness is a critical requirement for making high-quality optical devices. Chemical mechanical polishing (CMP) is an important process of smoothing surfaces for hard and brittle planar optics. Thus, there are growing interests in developing high-precision flatness on-machine measurement system for tin plate CMP process. However, the traditional evaluation measurement cannot meet the measurement accuracy requirement of approximate 2  μm. In this study, we propose an effective on-machine measuring system for the large-caliber optical tin plate, which consists of linear guideway, rotary table, and measuring sensor. In the system, the straightness error of the guideway and the axial runout error of the rotary table are compensated using a spiral method and the Keyence LK-G5000 measuring sensor. First, the spiral measuring path is formed by the movement of the line guideway and rotary table, which can prevent from multiple calibration. Then, the 3D flatness error of the dressing process is measured by linear movement of the LK-G5000 and the rotation of the tin plate. After the primary measurement process, the obtained 3D flatness error is compensated for straightness and axial runout error in sequence. To verify the accuracy of the flatness measurement, the tin plate is dressed by the natural diamond tool according to the measured 3D flatness error. After the dressing process, the peak-valley value of the remeasured flatness error can achieve 2.12  μm through a single-step dressing. The experimental results provide the accuracy and reliability of the high-precision on-machine flatness measurement system for the large-caliber tin plate.

Due to the development of wearable smart/electronic integrated textiles, the heating compression bandages, conductive fabrics, and electrically heated garments have been extensively used in many fields. Heating garments could be widely applied in the field of body warming and physical therapy. To impart heating therapy through garments, we need to select conductive yarn to be incorporated into the fabric. In addition to this, voltage supply, resistance, temperature distribution, temperature gradient, heating area, and spacing between the two consecutive conductive yarns are some major factors that have to be optimized for heating garments. Therefore, identifying the proper conductive yarn and approximate spacing between them is important in the electrically heated garments. The measurement of temperature and temperature profile around heated textile conductive yarn is demonstrated using digital holographic interferometry (DHI). DHI has been widely used to measure temperature and temperature profile of gaseous flames and heat conduction studies, etc., as it is more accurate, precise, and provides better spatial resolution. DHI is chosen to measure temperature distribution around copper and stainless-steel yarns used in textiles. DHI is a noncontact, noninvasive, full-field, and almost real-time interferometric technique. We have chosen copper and stainless-steel yarn to study the temperature profile and uniform heating to approximate spacing between two yarns.

Fringe pattern denoising is of prime importance in phase demodulation, especially for a single fringe pattern in speckle interferometry. A fringe speckle noise removal algorithm using the Kalman filter is proposed. The conventional linear Kalman filter is implemented with a fixed value of the process and measurement noise covariances; the adaptive Kalman filter is implemented with the process, and measurement noise covariances are estimated in an adaptive manner. The fringe denoising is performed sequentially in a rowwise and columnwise manner. The simulated and experimental results demonstrate the practical applicability of the proposed method, and its performance is appraised using metrics such as the quality index, peak signal-to-noise-ratio, and speckle index.

To study the change of coaxiality of rotor shaft during laser cladding, a numerical simulation of the rotor shaft was carried out by ANSYS Workbench, and the temperature field and structure field of the rotor shaft were simulated and analyzed by indirect coupling of transient temperature field and transient structure field. The temperature distribution of the rotor shaft during laser cladding was obtained from the results of the temperature field. The maximum temperature is 2350°C, and the final temperature converges to about 2100°C. Then, the results obtained from the temperature field are entered into the structure field as loads, and the change of coaxiality of rotor shaft during laser cladding is obtained. Finally, the laser is used to clad Fe60 powder on the 45 steel rotor shaft, and the coaxiality of the rotor shaft after cladding is measured by Taylor cylindricity meter. The measurement results are basically consistent with the simulation results, and the error is <10  %  . It lays a good foundation for exploring the cladding mode or track that can maintain better coaxiality of rotor shaft in the process of laser cladding and is of great significance for the repair of damaged rotor shaft.

Magnification and distortion are two important parameters for high-precision imaging systems. Point diffraction interferometers (PDIs) can measure the magnification, distortion, and wavefront aberration of imaging systems with high precision. However, determining the precise pinhole alignment of the classical PDI is difficult. A new method for measurement of the magnification and distortion based on a dual-fiber point diffraction interferometer (DFPDI) is proposed. The end faces of two fibers are placed on the object plane of the optics under test and imaged to the image plane. The distance between the image points in the x and y directions are proportional to the Z2 and Z3 Zernike coefficients of the wavefront measurement result, respectively. The measurements of the image placement shift and precise alignment of the point diffraction pinhole are realized rapidly with high accuracy. The feasibility of the method is verified experimentally. The wavefront aberration, magnification, and distortion of a 5  ×   reduction lens with numerical aperture (NA) of 0.3 is measured jointly. The measurement uncertainties (3σ) of the magnification in the x and y directions and distortion are 756 ppm, 793 ppm, and 0.233  μm, respectively. Error analysis shows that the position error of the object- and image-plane stages is the main error source. An improved measurement scheme with a pinhole–pinhole pairs array in the object plane and a pinhole–window pairs array in the image plane is proposed. The influence of the position errors of the stages is eliminated with optimized measurement procedure. The DFPDI’s measurement repeatability (3σ) of the Z2 and Z3 coefficients is 0.65 and 0.33 nm, respectively, corresponding measurement uncertainties (3σ) of the magnification (in the x and y directions) and distortion can reach 1.88 ppm, 1.69 ppm, and 0.812 nm, respectively.

We propose a line structured light 3D measurement technology for pipeline microscratches based on a telecentric lens that realizes the 3D measurement of microscratches on the pipeline surface. A method for calibrating the light plane normal vector under the telecentric camera model is proposed. This method only needs to consider the orientation information in the light plane calibration without involving position information, which avoids the difficulty of calibrating the light plane due to the insensitivity of the telecentric camera to the depth changes of the object along the optical axis. The self-adaptive convolution-mass method is used to extract the centerline points of the light stripe with speckles. Finally, the 3D coordinates of the intersection of the light plane and the measured surface are reconstructed. A line structured light micromeasurement platform based on a telecentric lens was built. Experiments show that the maximum standard deviation of the measurement is 2.0  μm, and the maximum error of the average value of repeated measurements is 0.3  μm, indicating that the measurement platform has high accuracy that meets the requirements for the measurement of the microscratch depth of pipelines in industrial applications.

A photoelectric reference ruler is designed based on position sensitive detector (PSD) for providing the reference length. A calibration method of the photoelectric reference ruler is proposed, which introduces the common points for transition between the PSD coordinate systems. The common points are confirmed based on the special workpiece with positioning holes. Through placing the 1.5-in. ball target on the positioning holes, the coordinate systems and the common points for transformations are structured by high-precision measurement instruments. After the calibration, the double-theodolites system is oriented by the photoelectric reference ruler and operated to measure the spatial points and distances in the experiment. The mean error is <0.18  mm in points measurement and <0.14  mm in distance measurement, and the feasibility of the proposed calibration method is validated. Compared with the traditional reference ruler, the photoelectric reference ruler is proved to be applicable for measurement system orientation and spatial large-scale measurement.

Chromatic confocal metrology is a widely established optical metrology technique, which allows for noncontact, high-speed three-dimensional surface profiling without the need of mechanical depth scanning. However, current methods are limited by the use of some sort of surface scanning method with mechanically moving parts. Furthermore, the setups involve a spectrometer setup, either through prisms, gratings, or multispectral cameras. This drastically limits the simultaneously measureable positions in lateral direction, as the spectrometer setup will utilize one spatial dimension for the wavelength domain. We present a method for chromatic confocal metrology that enables high-speed and high-resolution one-shot aerial surface metrology. This method is scalable with respect to measurement range in axial as well as in lateral direction and in the number of measurement points that can be measured simultaneously. After deriving the theoretical basis of the approach, a virtual optical design with a field of view of 10  mm  ×  10  mm and a depth range of 1.5 mm with roughly 1000 measurement points, based mainly on off-the-shelf components will be presented. This virtual system design was used to perform various simulations and explain the design process and considerations as well as the expected system response of the proposed system.

We propose a fiber optical cell catapult that is bird beak-shaped fiber cone optical tweezers that trap cells, then push them to the fiber tip via the evanescent fields on the side surface of the fiber cone, and finally eject them in a particular direction. The intensity distribution of the light field and the optical force of the fiber catapult are calculated by the finite element method. Moreover, an experimental study of the fiber catapult is given using yeast cells.

A noncontact displacement system suitable for tracking slow moving surfaces with low reflectivity is demonstrated. The displacement is measured by dynamic tracking of the moving focal plane of the sample under test. The system comprises a camera, a vertical digital piezo driver, and a data acquisition module. The tracking effect is achieved by continuously driving the sample with a 2-μm sweep around the focal plane, simultaneously acquiring the sample position and images of the part of the sample defined as a region of interest (ROI). The position of the focal plane is identified by fitting the contrast of the ROI versus the stage position to a Gaussian function. Using an ROI provides the ability to test various regions across the object and eliminates the demand for the surface to be flat or reflective. The system is low cost, is applicable to a large variety of samples and has an accuracy better than 10 nm.

Extracting phase from a single-frame fringe pattern is a key and challenging problem in fringe projection 3D measurement, especially for dynamic 3D measurement. We propose a single-shot phase extraction approach based on a low-pass filter with a well-trained image denoiser. Various comparative experiments have verified the effectiveness of the proposed method. More importantly, we associate the single-shot phase extraction problem with image denoising using deep learning. Thus more existing well-designed deep neural network models can be reused in the proposed method, without having to design a new model.

The littering of steel waste increases annually, and it causes environmental pollution and resource wastage. Rapid classification of steel is a critical step in the process of recycling to conserve resources. The method of principal components analysis (PCA) combined with support vector machine (SVM) was developed to establish a model for rapidly classifying 14 kinds of special steel samples, whose spectra were acquired via a portable fiber-optic laser-induced breakdown spectroscopy (FO-LIBS) system. Fifty-one preselected characteristic lines of trace elements were chosen as input variables because the samples of special steel differed in terms of the concentration of trace elements. Results showed that the recognition accuracy of the PCA-SVM model was gradually improved by the increase in principal components (PCs) and reached 100% when 13 PCs were extracted as input; this accuracy value was significantly higher than the 95% accuracy of the SVM model. This finding suggests that FO-LIBS combined with the PCA-SVM algorithm can achieve rapid classification of steel materials and provide a new approach for online detection in the industrial field.

We demonstrate a single-shot uniaxial three-dimensional (3D) profilometry system that illuminates a sample with a color structured polarization pattern with an axial chromatic aberration. We have previously shown that real-time 3D shape measurement can be performed without the occlusion problem using a polarization camera and a monochromatic polarized pattern. Here, we show that it is possible to double the depth range of the system, with no tradeoff in depth resolution, measurement speed, or accuracy, using color pattern projection and an RGB polarization camera. We present the measurement principles of the system and show the results of a real-time 3D profilometry experiment for a sample with a deep hole.

Broad spectra are of interest for a variety of applications, including pulse compression and ultrafast optical signal processing. We report a scheme of a cascaded chirped quasi-phase-matching (QPM) grating with a complementary reciprocal lattice vector bandwidth. The large reciprocal lattice vector bandwidth provided by first- and second-order QPM can simultaneously achieve second and third harmonic generations. Combined the effective nonlinear coefficient model with the transfer function method, it reveals that spectrum width increased with increasing fundamental wave bandwidth, reciprocal lattice vector bandwidth, chirp rate, and crystal length. The two-section cascaded chirped QPM grating can offer a reciprocal lattice vector bandwidth as large as 0.3 to 1.26  μm^−  1, which corresponds to a broadband spectrum covering 450 to 820 nm upon illumination with a tunable femtosecond laser. The proposed grating could extend supercontinuum generation toward potential spectroscopic applications.

Our research investigates an optical channel deaggregation technique based on modulation format conversion that may be used in elastic optical networks (EONs) to achieve high spectral efficiency, flexibility, and high data rate. The modulation format conversion technique from 8-ary phase shift keying (8-PSK) to two simultaneous quadrature phase shift keying (QPSK) at 50  Gb  /  s has been simulated and investigated. 8-PSK and the converted QPSK signals are investigated and compared in terms of bit error rate (BER) and quality factor (Q-factor), and it is demonstrated that they substantially reduce the complexity of transmission and reception process, at high data rates in EON. Additionally, this approach is further exploited to tailor a protection scheme for network survivability. Channel deaggregation, which divides the channel into working and protection paths, is used to implement a dedicated path protection scheme in EON. To evaluate the effect of various network conditions such as traffic load, modulation format, and BER on EON survivability, network simulations are performed on the ARPANET network.

We present a novel 21-core homogeneous multi-core fiber (MCF) structure with three different types of core placement layouts (1-Ring, 2-Ring, and Square Lattice) and densely pack the cores with a minimum cladding diameter of 200  μm to support high-speed applications. In the first phase, three MCF structures (1-Ring, 2-Ring, and Square Lattice) were designed with a step refractive index (RI) profile under the limited cladding thickness and diameter of 35 and 200  μm, respectively, and their crosstalk was calculated. In the second phase, all three structures were designed with a low-RI trench-assisted (TA) profile to significantly reduce the crosstalk. To further suppress the crosstalk, air holes were placed between the TA cores, and it was found that the TA Square Lattice core arrangement with air holes achieved the minimum crosstalk value of approximately −70  dB  /  100  km. The impact of important design parameters, such as transmission distance, bending radius, operating wavelength, and core diameter on inter-core crosstalk for all three design structures for both RI profiles and air-hole arrangement were numerically analyzed. Furthermore, other transmission characteristics, such as group delay and dispersion concerning wavelength, were analyzed for the above-stated design structures.

Computer-aided alignment (CAA) is a key technology for improving the assembly efficiency and performance of optical systems. However, because of the coma-free pivot point in two-mirror optical systems (TMOSs), the wavefront aberrations from multiple fields of view (FoVs) are required to compute misalignments, and this is not practical. Therefore, misalignment-caused wavefront aberrations were investigated based on the nodal aberration theory, and an analytical aberration computation model for TMOSs was derived. Based on this, an efficient misalignment calculation method based on single-FoV aberrations that introduces known misalignments was proposed and tested by conducting Monte Carlo simulations using the Hilbert telescope. The results showed that micron-level precision can be achieved for the aberration and misalignment calculation without any measurement noise and that a greater number of introduced misalignments can decrease the effect of measurement noise, thereby verifying the effectiveness of the proposed model and method. The findings of this research will open a new direction in CAA by introducing the misalignment rather than the FoV.

Quantum key distribution can realize unconditional security of communication. Here, a quantum decoding chip based on silica-on-silicon planar lightwave circuit (PLC) platform, which is compatible for multiprotocol has been demonstrated. PLC technology provides stability, high integration, and practicality for the chip, whereas silica-on-silicon material makes it low loss and low cost. The chip is integrated with three variable optical splitters, two asymmetric Mach–Zehnder interferometers, and four variable directional couplers. The interference visibility is investigated by self-interfering method, and the results showed it is high to 98.2% under temperature control. The extinction ratio for the phase states is kept between 23 and 25 dB for 6 h without active phase correction.

The ever-increasing demand for global internet traffic, together with evolving concepts of software-defined networks and elastic-optical-networks, demand not only the total capacity utilization of underlying infrastructure but also a dynamic, flexible, and transparent optical network. In general, worst-case assumptions are utilized to calculate the quality of transmission (QoT) with provisioning of high-margin requirements. Thus, precise estimation of the QoT for the lightpath (LP) establishment is crucial for reducing the provisioning margins. We propose and compare several data-driven machine learning (ML) models to make an accurate calculation of the QoT before the actual establishment of the LP in an unseen network. The proposed models are trained on the data acquired from an already established LP of a completely different network. The metric considered to evaluate the QoT of the LP is the generalized signal-to-noise ratio (GSNR), which accumulates the impact of both nonlinear interference and amplified spontaneous emission noise. The dataset is generated synthetically using a well-tested GNPy simulation tool. Promising results are achieved, showing that the proposed neural network considerably minimizes the GSNR uncertainty and, consequently, the provisioning margin. Furthermore, we also analyze the impact of cross-features and relevant features training on the proposed ML models’ performance.

Engineering of optical alignment tolerance between a laser source and a Fabry–Perot (FP) cavity is of great importance in optimizing a laser analysis system and saving costs in the additional alignment task. We propose a modification of the conventional confocal FP (CFP) cavity–a symmetric nonconfocal FP (SNFP) cavity with two identical spherical mirrors separated by a distance equal to half of the common radius of curvature. Numerical analysis of the two cavities reveals that the SNFP cavity has better off-axis stability and much better angular misalignment tolerance than the CFP cavity, even with a longer optical path length (OPL). The SNFP cavity provides a six-transit path length for a basic cavity mode that supports a 1.5-fold long OPL within the same volume as the CFP cavity, which is favorable for applications requiring limits on the footprint and weight of the cavity. In addition, a ray-tracing simulation with a disk-type source having an angular Gaussian distribution (α  =  β  =  5  deg) reveals that the emission beam profile from the SNFP cavity is narrower than that from the CFP cavity. These results are expected to help reduce cavity loss and to improve alignment efficiency between the laser source and the FP cavity.

Due to the higher bandwidth requirements of the user, the multi-wavelength based next-generation Ethernet passive optical network (NG-EPON) has emerged to provide potential solutions for the wide-range coverage and to accommodate multiple consumers per fiber. In this paper, the stimulated Raman scattering (SRS) effect in NG-EPON systems is studied, where upstream and downstream wavelengths are both located in the O-band. The influence of SRS effect on the 4  ×  25G and 8  ×  25G NG-EPON wavelengths is investigated, and it involves two aspects, including the SRS-induced crosstalk and power depletion. For the former, owing to the short interaction time between upstream and downstream wavelengths, the SRS-induced crosstalk on the bit error rate (BER) performance of the 4-channel and 8-channel NG-EPON systems can be neglected. For the latter case, 1.3 dB power depletion can be subjected to the 4-channel NG-EPON system, when the launched power of the downstream wavelength is 12 dBm and the fiber length is 40 km. Furthermore, with the increase of number of channels, the SRS causes more severe impact on the 8-channel NG-EPON system, leading towards the 2.9-dB power depletion. The given results could be useful in providing practical contributions for the designing of future NG-EPON systems.

Microwave photonic channelized receiver is one of the important means to realize broadband radio frequency (RF) signal reception, and it also has great application potential in the fields of radar systems and electronic warfare. In view of the above, a microwave photonic channelizer with 66-subchannels based on acousto-optic frequency shifter (AOFS) is proposed. The 11-line optical frequency comb (OFC) used in this scheme is generated via one phase modulator. The 33 optical local oscillators can be obtained using two AOFSs to shift the frequency of 11-line OFC up and down. The 33 optical local oscillators and broadband RF signal are image-rejected and downconverted in the I  /  Q receiver and output by 66 subchannels with a bandwidth of 500 MHz. The simulation results verify the complete reception of 3 to 36 GHz wideband RF signal, and the spurious-free dynamic range of the system can reach 116.3  dB  ·  Hz^2/3.

Recently, visible light communication (VLC) has become a hot topic owing to its advantages, such as high security, high capacity, and antielectromagnetic interference. VLC has become a potential candidate for indoor access networks due to the feasibility of combining illumination and communication. However, intersymbol interference and random phase rotation induced by the transmission channel will decrease the system performance. Traditional constant modulus algorithm (CMA) performs well in converging constellation, but random phase rotation still exists since CMA is insensitive to phase. We demonstrate an optical fiber and visible light integrated communication system. 960-Mbps multiband geometrically shaping (GS) quadrature amplitude modulation (QAM)-8 transmission is realized. Modified learning vector quantization is employed after CMA equalization to mitigate the impairment induced by both optical fiber and visible light channel. Experimental results indicate the feasibility of the proposed method. The Q factor of GS QAM-8 could be enhanced by 5.98 dB with the proposed method.

In a high-power underwater wireless optical communication (UWOC) system, the bandwidth limitations of high-power optical sources and high-sensitivity detectors and the multipath effect of seawater channels can cause intersymbol interference, which seriously affects the performance of the UWOC system. Based on the attenuation characteristics and time-domain broadening characteristics of underwater wireless optical signals, a dual-mode adaptive switching blind equalization algorithm is proposed; it combines the variable step size constant-to-mode fractional spaced equalizer (FSE) algorithm and the decision directed least-mean-square mode-FSE algorithm to improve the performance of long-distance UWOC systems. Simulations show that the proposed algorithm has antinoise performance under different seawater qualities. In particular, with a bit error rate performance of ^{10  −  4} in coastal seawater, the signal-to-noise ratio of the proposed algorithm is 5.2 dB lower than the traditional constant-to-mode decision directed least-mean-square algorithm and 9.2 dB lower than that when the algorithm is not equalized.

The analysis of the polarization characteristics of reflected light and backscattered light can provide theoretical support for the research on key technologies of underwater active light source polarization imaging. The influence of the parameters of different light sources, environments, and reflective targets on the characteristics of the reflected light was analyzed. The difference in the degree of polarization between the reflected light and the backscattered light was also determined. A Monte Carlo numerical simulation method based on a combination of Mie scattering theory and polarimetric bidirectional reflectance distribution function was used to establish underwater photon scattering and reflection-tracking models. Through simulation and analysis of the influence of the underwater environment system on the polarization characteristics of the backscattered photons and the reflected photons of different polarization types of the incident light, the following conclusions are drawn. First, in the same condition, the difference in polarization characteristics of backscattered and reflected light of circularly polarized light was larger than linearly polarized light. This is due to the better polarization-maintaining ability of circularly polarized light than linearly polarized light. Second, when various types of materials were used as reflective targets, the difference in their complex refractive indices changed the polarization of the reflected photons. And the complex refractive index had varying effects on the two types of polarized light.

Network virtualization has been considered one of the promising paradigms for future network architecture, which can satisfy the diversified and personalized requirements of different applications by sharing physical network infrastructure. One of the major challenges in virtualization is how to map virtual networks efficiently onto the substrate network considering different constraints. We aim at solving the problem of high energy consumption of virtual network embedding in respect of the orthogonal frequency division multiplexing using elastic optical networks (EONs). First, we comprehensively consider and design an energy consumption model of network components, which denotes the key part of virtual optical network embedding (VONE). Then, a dynamic heuristic energy-efficient virtual optical network embedding (DEE-VONE) algorithm is proposed to achieve high energy efficiency and resource scalability. Simulation experiments have proven that, compared with the two benchmark algorithms, namely, the FFK-VONE and LRCK-VONE, the proposed method can maximize the network energy consumption saving at the cost of increasing the blocking probability. As the traffic load increases, the DEE-VONE method achieves higher energy-saving efficiency because optical switching energy saving plays an essential role.

We present a weakly coupled bow-tie rectangular dual-step few-mode fiber supporting 20 eigenmodes for short-haul communication systems across the O band. The rectangular dual-step core and bow-tie stress-applying area are introduced to effectively split adjacent eigenmodes. We evaluate the impact of parameters on modal mode effective refractive index difference (MERID) Δn_eff, min Δn_eff, min A_eff, B_m, and bending loss at a wavelength of 1310 nm. Broadband performance of the entire O band, including n_eff, MERID Δn_eff, differential mode delay, and dispersion, is also analyzed. Results indicate that the 20 eigenmodes supported by the designed fiber are completely separated with MERID Δn_eff between adjacent modes larger than 2.319  ×  ^{10  −  4} over the whole O band. The designed fiber can be used for short-haul multiple-input multiple-output-free eigenmode-division multiplexing systems to improve transmission capacity and expand bandwidth.

Two approximate closed-form probability density function expressions for the sum of lognormal-Rician random variates (RVs) and the sum of square root of lognormal-Rician RVs are obtained. The proposed expressions are shown to provide high accuracy over a wide range of channel conditions according to Kolmogorov–Smirnov goodness-of-fit statistical tests results. Also, the analysis of the approximation error is presented to indicate that a higher approximation accuracy can be achieved for larger r or smaller variance σz2. To reveal the importance of the proposed approximation, new approximate closed-form expressions of the ergodic capacity, average bit error rate for the intensity-modulation direct-detection (IMDD), and coherent multiple-input multiple-output (MIMO) free-space optical (FSO) systems with equal gain combining diversity technique over lognormal-Rician turbulence channels are developed. It is observed that MIMO technology can offer a significant improvement in system performance and the performance of coherent FSO systems outperforms that of IMDD systems. The Monte Carlo simulation results are further utilized to illustrate the accuracy of the proposed approach.

We present a photodetector sensor that is able to perform preprocessing operations on the focal plane. Each pixel can be connected with any of its neighbors in order to implement detection zones defined by software. The output current of the sensor is a customizable weighted sum of the currents sourced at the defined detection zones. This characteristic leads to applications related to pattern matching. Two examples are shown in our work: one is related to speckle correlation for real-time vibration detection, and the other one is an alternative image recording method that is the first step to an on-hardware compressed sensing technique.

A low-loss 1  ×  256 optical power splitter is designed and fabricated using silica-based planar lightwave circuit technology on a 6-in. quartz substrate. The measured results show that the insertion loss, uniformity, and wavelength-dependence loss (WDL) of a 1  ×  256 splitter are <26.2, 1.97, and 1.83 dB, respectively, in the wavelength range from 1.26 to 1.63  μm. The insertion loss, uniformity, and WDL of a 1  ×  256 splitter are <25.62, 1.33, and 1.03 dB, respectively, in the normal communication wavelength range from 1.31 to 1.55μm. The polarization dependence loss is <0.16  dB in the wavelengths of 1.31 and 1.55  μm.

An ultrawideband polarization rotator (PR) with low insertion loss (IL) based on silicon on insulator (SOI) platform is proposed. The input TM₀  /  TE₀-polarized modes can be rotated 90 deg simultaneous using a 45-deg W-slot dual-stair waveguide with varied width. Simulation results show that with a PR in length of 4.3  μm, the IL is below 0.4 (0.42) dB and polarization extinction ratio (PER) is over 17 (16) dB for TE₀-to-TM₀ (TM₀-to-TE₀) mode conversion within bandwidth of 300 nm (from 1400 to1700 nm), which covers optical fiber communication S-, C-, L-, and U-bands. In addition, the fabrication tolerance is analyzed numerically. The proposed PR has excellent performance with compact footprint and will find potential application in large-scale high-performance PICs.

A novel, low-cost, camera-based method of detecting a single nanosecond (ns) laser pulse and kHz modulated continuous wave and pulsed lasers has been developed. The detector uses a simple optical modification to a standard rolling shutter color camera combined with image processing techniques to distinguish lasers from other illumination sources and extract a laser’s wavelength and pulse repetition frequency. In addition, the detector is also capable of detecting a single ns laser pulse at any given time. Such a detector has applications in free-space optical communications (FSO comms) as a low-cost broadband method of extracting information from multiple sources and as a detector of laser range finders. A low-cost prototype (≈£600) has been developed using entirely off-the-shelf components and assessed in laboratory and field trial conditions, with the ability to measure laser wavelengths to ±5  nm and pulse repetition frequencies to within ±5  %   at a distance of 660 m. In the laboratory, the prototype was also able to detect each of the 1000 pulses generated by a 10 Hz 10 ns 532-nm pulsed laser, as well as 100 pulses sent at random intervals, highlighting its capability to detect a ns pulse at any given time. This novel technology offers a low-cost method of detecting lasers and extracting their pulse repetition frequencies, with a wide field of view and high spatial resolution. Ultimately, this technology has applications in FSO comms for between vehicles or platforms of interest, with a capability of communicating with multiple targets simultaneously.

Surface-enhanced Raman spectroscopy (SERS) is a powerful technique for the detection of natural dyes, allowing one to overcome the limitations of conventional Raman spectroscopy, i.e., the weakness of the signals and the intense fluorescence background. In the artistic field, a noninvasive approach is recommended; however, SERS is still an inherently invasive method, requiring the extraction of the analyte or close contact with the object and wet substrate. Inexpensive and easy-to-produce substrates allowing for dry-state measurements were fabricated, exploiting only the electromagnetic interaction between a nanostructured substrate and the dye molecules absorbed onto a textile. To this aim, different substrates were developed starting from two colloids (silver nanospheres and nanostars) immobilized onto a functionalized microscope glass slide, and some parameters connected to their synthesis were optimized to obtain a great enhancement of the signal in dry conditions. Finally, dry-state SERS spectra of four different dyes were successfully obtained from reference dyed wool threads.

We introduce structures of sensors based on defective one-dimensional quinary photonic crystals. The unit cell of the structure is composed of five layers of N-BAF10  /  KNbO₃  /  TiO₂  /  KNbO₃  /  N-BAF10, whereas blood cells under investigation are supposed to construct a defective layer in the middle of the structure. The basic principle of detection of the proposed sensor is based on the existence of the resonant mode, within the photonic bandgap of the transmittance spectrum, due to the presence of blood cells in the defect layer. We found that the characteristics of the resonant mode are dependent on the type of blood cells used, thickness of the defect layer, and the angle of incidence of radiation. The average values of sensitivity, quality factor, and figure of merit for all types of cancerous blood cells are found to be about 623  nm  /  RIU, 129,560, and 73,950, respectively, at normal incidence. These values increased to 717  nm  /  RIU, 426,000, and 318,600, respectively, as the angle of incident increased from 0 deg to 45 deg with a low limit of detection of 1.998  ×  10^−  7 at 45 deg. Our results indicate that the proposed structures are very efficient in sensing and identifying the type of cancerous blood cells.

We demonstrated that visible surface plasmon polaritons (SPPs) were excited at the metallized interface of indium-tin-oxide (ITO)-coated iron doped Y-cut and Z-cut lithium niobate (Fe  :  LiNbO₃, Fe:LN) slabs, where large angle scattering and light tracks were observed on the surface. After introducing active erbium element, it was found that SPPs’ excitation could greatly affect upconversion emission (UCE) in Er,Fe:LN crystal samples. This surface effect was more attractive when increasing the surface-to-volume ratio with powdered form. In the ITO-coated Er,Fe:LN specimen, dynamic variations of huge UCE dropping-down and gradual rising were observed, which is a result of energy loss via coupling to SPPs. Our work supports an opportunity in designing plasmonic nanometric light sources, leading paths toward implementing spasers apart from lossy metals in photonic waveguides.

We developed a convolutional neural network-based high-sensitivity gas optical sensor (CNN-HGS) using photonic crystals for detecting different gases (N₂, He, and CO₂). Square-shaped dielectric rods with a cubic lattice index were used for the maintenance of the exact distance and area between the rods. The flower pollination optimization algorithm was used for the improvement of the hyperparameters of the CNN. The proposed CNN-HGS consists of three resonance nanocavities: one nanocavity with a refractive index of 2.6 located at the center and the other two subnanocavities with a refractive index of 2.1 placed in the path of the input and output waveguides, respectively. The experiment for the proposed CNN-HGS was conducted with three certified sample gas cylinders and a precise mass flow controller. A clean air generator was linked to the same pipeline for the dilution of the flow of hydrocarbon. During the experiment, a typical gas admixture with concentrations of 60 to 900 ppm was used. Training and testing were conducted using a dataset with 80% and 20% of the total, respectively. The result shows that the proposed optimized CNN delivers a 7.5% improvement in the training accuracy. The CNN-HGS was tested and compared with three other optimization techniques, and the result shows the superiority of the proposed method.

A simple D-shaped photonic crystal fiber (D-PCF) with silicon-nano-crystal enrichment is proposed, with substantial nonlinearity, ultrahigh birefringence, and a higher degree of transverse resolution. To scrutinize the optical properties of the suggested D-PCF, the full vector finite-element method has been employed with an anisotropic perfect matched layer added around the designed model as a boundary condition. An elliptical air hole is being used as the core region of this simple structure, and thus it can achieve the most desirable property birefringence in the order of ^{10  −  2}. Tight mode confinement inside the core region benefits the large Kerr nonlinearity (γ) of 2.8  ×  10⁵ and 2.3  ×  10⁵  W^−  1 km^−  1 for X and Y polarization modes, respectively, at a wavelength of λ  =  1.55  μm. Meanwhile, the numerical aperture is extraordinarily high, exceeding 0.60, with many applications in optical coherence tomography and other related fields. Due to the simple design and low air filling fraction, the D-PCF is feasible for practical realizations in many sectors.

We present a design of an all-optical 4 to 1 multiplexer by cascading four stages of ψ-shaped three-input AND gates and a Y-shaped four-input OR gate on a square lattice photonic crystal with rods in air interface. The three-input AND gate was designed separately to achieve efficient logical output and integrated into the multiplexer, and the OR gate design was subsequently incorporated with the multiplexer design. The band diagram of the proposed structures was computed using the plane wave expansion method, and the electric field distributions were estimated using the finite-difference time-domain method. The all-optical three-input AND gate had a normalized intensity of 90% for logic “1” and 10% for logic “0,” a contrast ratio (CR) of 9.54 dB, a response time of 0.816 ps, and an operating bit rate of 1.224  Tb  /  s with a footprint of 189  μm². The all-optical 4 to 1 multiplexer had a normalized intensity of 79% for logic “1” and 2% for logic “0,” a CR of 15.96 dB, a response time of 0.848 ps, and an operating bit rate of 1.179  Tb  /  s with a footprint of 1040  μm². Therefore, the proposed 4 to 1 multiplexer design would be a desirable structure for optical signal processing and photonic integrated circuits.

The strong evanescent field of micro/nanofiber enables it to have a stronger interaction with the outside world and to better sense the changes of the external environment, thus realizing many types of chemical, biological, and environmental sensors. We applied micro/nano-optics for ocean exploration and proposed a sensing probe based on an elliptical microfiber. The sensor probe utilizes the stability of polarization intermode interference of an elliptical fiber and the high sensitivity of the microfiber evanescent wave coupling to achieve a high accuracy measurement of seawater salinity. Laboratory salinity sensitivity of 45.6 nm/% was achieved under seawater environment using an elliptical microfiber with a diameter of 2.8  μm and an ellipticity of 0.3, which is two or three orders of magnitude higher than that of conventional salinity measurements. This sensing probe is used to measure the salinity of seawater in the coastal area of Qinhuangdao, samples were taken for 7 days in September, and the average salinity of the seawater was measured to be 2.956%, which is basically consistent with the data in the Marine Environmental Impact Assessment Report Form of Qinhuangdao Government Service Center.

A bi-function switchable metasurface structure is proposed to realize dynamic switch function between ultrabroadband terahertz absorber and polarization converter. The structure consists of a SO₂ hemisphere in a square lattice, two different radius hybrid gold-photosensitive silicon rings cladding configuration, and metal substrate. When the conductivity of the photosensitive silicon is 1.0  ×  10⁴  S  /  m (i.e., in the metallic state), the metasurface structure exhibits ultrabroadband terahertz absorber with above 90% absorption in the range of 3.96 to 10.0 THz. The high absorption performance can be maintained before incident angle of 50 deg. When the conductivity of the photosensitive silicon is 2.5  ×  10^−  4  S  /  m (in the dielectric state), the proposed structure serves as a terahertz polarization converter. The polarization conversion rate (PCR) is larger than 90% from 3.88 to 7.21 THz within the incident angle range of 0 deg to 80 deg. By changing the conductivity of the photosensitive silicon, absorbance and PCR can be dynamically adjusted. The scheme provides a new perspective to explore multifunction terahertz device.

A simple and effective phase demodulation method is 3  ×  3 coupler demodulation, owing to its simpler structure than phase-generated carrier demodulation. However, it is difficult to obtain ideal demodulation results because of the diversity of noise sources in an optical fiber sensor system, particularly due to polarization fading. We present a noise processing method based on morphological filtering. First, the characteristics of various noises and their effects on the demodulation of a 3  ×  3 coupler are analyzed. Subsequently, the polarization fading phenomenon in a single-mode fiber is analyzed, and the effect of polarization fading on the elliptic fitting demodulation of 3  ×  3 couplers is described. The method uses morphological filtering based on an elliptic template to overcome the distortion in the demodulation signal due to polarization fading and other factors. Simulation and experimental results show that the proposed method can improve the stability and precision of phase demodulation technology based on the 3 × 3 coupler.