This PDF file contains the editorial “Impact Factor and Optical Engineering” for OE Vol. 49 Issue 12

In this paper, a novel image-based fusion video enhancement algorithm is proposed for night-time video surveillance applications by a combination of illumination fusion and based on moving objects fusion. The proposed algorithm fuses video frames from high quality day-time and night-time background with low quality night-time videos. For improving the perception quality of the moving objects, based on moving objects of region fusion method is proposed. Experimental results show the effectiveness of the proposed algorithm.

The H.264/AVC deblocking filter pays little attention to intracoded blocks. We enhance this filter by extending it to use intraprediction mode information in its adaptive application to the intracoded block. Experiments show its higher coding efficiency, with blocking artifacts sufficiently minimized in intracoded blocks.

Multiple surface plasmon resonances are experimentally observed for p-polarized as well as s-polarized incident light at the planar interface of a metal and a chiral sculptured thin film. These experimental results confirm that four surface plasmon resonances can be supported at the interface of metal-chiral sculptured thin film. Multiple surface plasmon resonances may allow for multiple simultaneous measurements by devices that utilize surface plasmon resonance for detection.

We describe an analytical and numerical method to design and optimize LED (light-emitting diode) collimators. The optimization process is confirmed by optical simulations and experimental measurements of a scaled prototype. The collimator's definitive geometry and design parameters rely on the LED's emitting characteristics and the employed collimator material. The resulting parabolic-elliptical-based collimator shows an optimum performance and a compact structure with requirement for mirrored surfaces.

A new nonparametric method, based on the smooth weighted-minimum-norm (WMN) focal underdetermined-system solver (FOCUSS), for electrical cerebral activity localization using electroencephalography measurements is proposed. This method iteratively adjusts the spatial sources by reducing the size of the lead-field and the weighting matrix. Thus, an enhancement of source localization is obtained, as well as a reduction of the computational complexity. The performance of the proposed method, in terms of localization errors, robustness, and computation time, is compared with the WMN-FOCUSS and nonshrinking smooth WMN-FOCUSS methods as well as with standard generalized inverse methods (unweighted minimum norm, WMN, and FOCUSS). Simulation results for single-source localization confirm the effectiveness and robustness of the proposed method with respect to the reconstruction accuracy of a simulated single dipole.

There has been a considerable recent increase in the use of variable focal length lenses (VFLLs), especially as microlenses in photographic objectives, endoscopes, microscope objectives, etc. One distinguishing feature of these VFLLs is the presence of a mechanism whereby the shape of the lens and its geometrical parameters can be changed. A new type of variable focal length lens is introduced made from elastic material. It is placed inside a mechanical mount where radial forces can be applied to its perimeter. We also present the optomechanical design and the measurement of wavefront aberrations to the third and fifth order of a solid elastic lens (SEL). A point-diffraction interferometer is used as a wavefront sensor to test changes of the lens. Geometrical changes in the lens produce changes in the aberrations. Finally, the aberrations found in the SEL (without any application of stress) are compared with aberrations obtained by means of numerical ray trace. Some experimental results are also shown.

A multiresolution 3-D measurement system using multiple cameras and a light sectioning method is developed to measure complex-profile objects for which other optical measuring methods are less suited. The system is composed of four cameras, which can select different system parameters to measure the whole profile and some details of an object at the same time. Thus, the system has a multiresolution measuring feature. We mainly focus on the imaging system model, system calibration, and the data merging method, and furthermore propose a calibration method with a self-designed planar calibration target and a data merging algorithm based on empirical mode decomposition. Experimental results show that position uncertainty of a measured point within the section plane is less than 0.06 mm in a 80×80-mm² measurement range. The system is employed to measure a blade and a gear with relatively satisfactory results.

Coded structured light can rapidly acquire the shape of unknown surfaces by projecting suitable patterns onto a measuring surface and grabbing distorted patterns with a camera. By analyzing the deformation patterns appearing in the images, depth information of the surface can be calculated. This paper presents a new concise and efficient mathematical model for coded structured light measurement system to obtain depth information. The interrelations among model parameters and errors of depth information are investigated. Based on the system geometric structure, the results of system parameters affecting object imaging can be obtained. Also, the dynamic deformation patterns can be captured under different measurement conditions. By analyzing the system parameters and depth information errors, the system constraint conditions can be determined, and the system model simulation and error analysis are discussed in experiments, too. Also, the system model based on optimal parameters is utilized to implement reconstruction for two objects.

The destruction of spatial complex tubular joints may lead to failure of the whole tubular structure, thus it is necessary to analyze the mechanical properties of spatial complex tubular joint. In this paper, a novel method based on close range photogrammetry to accurately measure the three-dimensional (3D) deformation of spatial complex tubular joints during loading test is proposed. Artificial targets are pasted on the deformation area before loading. The 3D coordinates of these targets are reconstructed by analyzing the images captured at each stage, and the coordinate systems of different stages are registered together by means of global transformation points. The whole field 3D deformation under different load levels is then obtained by tracking the homonymous targets among different stages. It is helpful for further analysis of the mechanical properties. Two different precision evaluation experiments indicate that the proposed method could achieve accuracy of 0.1mm/m. Two full scale tubular joints are tested and a feasible solution for improving the load carrying capacity of the tested tubular joints is thus obtained as per the measured results. For comparison, finite element analysis is employed to predict the deformation in a traditional way. The deformation tendency measured by two methods agrees well.

A more simplified photonic microwave frequency measurement configuration based on a loop mirror filter is proposed and experimentally demonstrated. It is implemented by propagating a carrier-suppressed double-sideband modulated optical signal through a loop mirror filter. The ratio between the optical powers of the two output ports provides a direct measurement of the unknown signal frequency. This scheme can solve the main problems that exist in previous work. A proof-of-concept experiment is performed with a measurement range of 6 to 18 GHz and resolution less than 0.35 GHz.

We demonstrate an optical probe for detection of porosity inside spool bores of a transmission valve body with diameters down to 5 mm. The probe consists of a graded-index relay rod that focuses a laser beam spot onto the inner surface of the bore. Detectors, placed in the specular and grazing directions with respect to the incident beam, measure the change in scattered intensity when a surface defect is encountered. Based on the scattering signatures in the two directions, the system can also validate the depth of the defect and distinguish porosity from bump-type defects coming out of the metal surface. The system can detect porosity down to a 50-µm lateral dimension and ~40 µm in depth with >3-dB contrast over the background intensity fluctuations. Porosity detection systems currently use manual inspection techniques on the plant floor, and the demonstrated probe provides a noncontact technique that can help automotive manufacturers meet high-quality standards during production.

The influences of thermo-chemical reduction processing on the physical properties of lithium niobate are studied. The behavior of the surface resistivity and the induced optical absorption are characterized, with trends indicating a significant reduction in resistivity can be realized before absorption becomes problematic in the 1.0 µm spectral region. The edge localization of the effects in bulk materials is identified, suggesting a central clear aperture of high transmission is possible even when large absorption near the crystal edges is observed. Electro-optical Q-switch crystals were processed with varying degrees of annealing and reduction, leading to the realization of several samples with optimal combinations of modified surface and bulk properties. The highest transmission samples were then tested under transient ambient temperature conditions and compared to unprocessed crystals. The processed samples showed a significant reduction in the transient depolarization of transmitted laser light due to the pyroelectric effect.

By using vanadium-ion-doped YAG crystal (V³⁺:YAG) as a saturable absorber, a xenon-lamp-pumped passively Q-switched and mode-locked (QML) Nd:YAG laser at 1.34 µm is realized in a straight cavity. About 90% modulation depth of mode locking of the pulse is obtained. The pulse energy and the pulse width of the QML laser are measured. Under the plane-wave approximation, considering the pump rate and the stimulated radiation lifetime of the active medium as well as the excited-state lifetime of the saturable absorber, modified coupled rate equations are introduced to reconstruct the xenon-lamp-pumped passively QML laser with V³⁺:YAG. By solving the equations numerically, the theoretical evaluations are found to be in good agreement with the experimental results. The numerical simulation results demonstrate that the model under the plane-wave approximation is accurate enough to describe the dynamical process of xenon-lamp-pumped passively QML laser with V³⁺:YAG.

The bandwidth and residual phase noise of optical phase-locked loops (OPLLs) using semiconductor lasers are typically constrained by the nonuniform frequency modulation response of the laser, limiting their usefulness in a number of applications. It is shown in this work that additional feedback control using an optical phase modulator improves the coherence between the master and slave lasers in the OPLL by achieving bandwidths determined only by the propagation delay in the loop. A phase noise reduction by more than a factor of two is demonstrated in a proof-of-concept experiment using a commercial distributed feedback semiconductor laser.

In the lidar-dial method, the amount of the water vapor present in the smoke of the vegetable fuel is detected to reduce the number of false alarms. We report the measurements of the smoke backscattering coefficients for the CO₂ laser lines 10R20 and 10R18 as determined in an absorption cell for two different vegetable fuels (eucalyptus and conifer). These experimental backscattering coefficients enable us to determine the error to be associated to the water vapor measurements when the traditional first-order approximation is assumed. We find that this first-order approximation is valid for combustion rates as low as 100 g/s.

We report a novel micro-optical systems approach for gas chromatographic detection based on plasma excitation of the eluate and subsequent emission spectroscopic evaluation. Specifically, we propose a detector architecture that integrates a microhollow cathode setup and an optical collector system on a common planar microsystems platform. The collector consists of an array of identical imaging systems that surround the microplasma and couple the emitted light side-on into fibers via which it can be fed into a spectrometer. Elliptically shaped reflector profiles ensure nearly aberration-free achromatic imaging and hence a high coupling efficiency. This is confirmed by ray-tracing simulations. An experimental demonstration of the detector module is assembled. The elliptical profiles are milled out of aluminium with diamond tools on an ultraprecision machining center. Experimental tests with a He plasma prove that a higher optical coupling efficieny than with the traditional end-on signal pickup scheme can be achieved.

We report a technique to substantially boost the spectral bandwidth of a conventional waveguide grating coupler by using a solid immersion cylindrical lens at the aplanatic condition to create a highly anamorphic beam and reach a much larger numerical aperture, thus enhancing the spectral bandwidth of a free-space propagating optical beam coupled into a single-mode planar integrated optical waveguide (IOW). Our experimental results show that the broadband IOW spectrometer thus created almost doubles (94% enhancement) the coupled spectral bandwidth of a conventional configuration. To exemplify the benefits made possible by the developed approach, we applied the technique to the broadband spectroscopic characterization of a protein submonolayer; our experimental data confirm the enhanced spectral bandwidth (around 380-nm) and illustrate the potentials of the developed technology. Besides the enhanced bandwidth, the broadband coupler of the single-mode IOW spectrometer described here is more robust and user-friendly than those previously reported in the literature and is expected to have an important impact on spectroscopic studies of surface-adsorbed molecular layers and surface phenomena.

Based on the scalar four-photon scattering process, the quantum state of a lightwave at the output of fiber is derived by solving the nonlinear Schrödinger equation with a perturbation theory. The joint spectral function of two photons is achieved from the derived quantum state. The dispersion operator involves the third-order dispersion term in the case that the pump wavelength is close to the zero dispersion wavelength. Simulation results show the first-order approximation of our joint spectral function is in excellent agreement with the complicated exact solution. By analyzing the spectral property of the two-photon flux generated by four-photon scattering in photonic-crystal fibers, it is found that the sign of dispersion has very little influence on the spectrum except the slight modulation instability in the anomalous dispersion domain.

Mode splitting of higher order modes in elliptical dielectric waveguides has been addressed theoretically in great detail since the 1960s. This work presents for the first time detailed experimental measurements of mode splitting in elliptical core optical silica fibers, with a semiminor to semimajor ratio ranging from 1.0 to 0.1. The experimental data are compared with numerical simulations obtained from finite element calculations performed on fiber 2-D refractive index profiles from each of the studied fiber pieces.

A novel system of an optical vortex generation using an add/drop multiplexer incorporating with two nanoring resonators is proposed. Such a system is known as a PANDA ring resonator structure, in which the optical vortices (gradient optical fields/wells) can be generated and used to form the photon/atom trapping tools in the same way as the optical tweezers. By controlling some suitable parameters of the input and the control optical pulses, the intense optical vortices can be generated within the PANDA ring resonator, in which the trapped photons/atoms can move dynamically within the system. The trapping force occurrs and is formed by the combination between the gradient field and scattering photons, which we review. A transmitter and receiver can be formed within the same system (device), which is called a transceiver. Finally, the use of the PANDA ring resonator as a hybrid transceiver and repeater for nanocommunication is discussed.

An optical 90-deg hybrid of birefringent crystals for freely propagating laser beams is presented. It consists principally of a quarter-wave plate, two pairs of birefringent crystal plates, and a polarization analyzer. The splitting and recombination of the signal and local-oscillator beams are achieved through the birefringence of the crystals, and a 90-deg phase shift is introduced between orthogonally polarized beam components by use of a quarter-wave plate. The optical hybrid has a self-compensating light path, and its correct function is demonstrated in a self-heterodyne measurement setup.

We present an experiment demonstrating the spectral-polarization coding optical code-division multiple-access system introduced with a nonideal state of polarization (SOP) matching conditions. In the proposed system, the encoding and double balanced-detection processes are implemented using a polarization-diversity scheme. Because of the quasiorthogonality of Hadamard codes combining with array waveguide grating routers and a polarization beam splitter, the proposed codec pair can encode-decode multiple code words of Hadamard code while retaining the ability for multiple-access interference cancellation. The experimental results demonstrate that when the system is maintained with an orthogonal SOP for each user, an effective reduction in the phase-induced intensity noise is obtained. The analytical SNR values are found to overstate the experimental results by around 2 dB when the received effective power is large. This is mainly limited by insertion losses of components and a nonflattened optical light source. Furthermore, the matching conditions can be improved by decreasing nonideal influences.

Digital holography captures holograms by charge-coupled device or complementary metal-oxide semiconductor cameras, which have a spatial resolution still not reaching that of silver-halide holofilms. Thus, due to the sampling theorem, the angle between the reference and object wave is limited. Only fields coming from small objects, objects far away, or optically reduced fields can be recorded. Here we investigate optical reduction by a system of lenses, and show that a system of two concave lenses results in a drastic reduction of the object-target distance, while the effect of using more lenses is insignificant. Experimental results obtained with Fresnel and lensless Fourier-transform geometry are presented, and implications on holographic interferometric metrology as well as on holographic 3-D television are given.

A novel index-of-refraction material-characterization technique using passive polarimetric imagery degraded by atmospheric turbulence is presented. The method uses a variant of the LeMaster and Cain [J. Opt. Soc. Am. A 25(9), 2170-2176 (2008)] blind-deconvolution algorithm to recover the true object (i.e., the first Stokes parameter), the degree of linear polarization, and the polarimetric-image point spread functions. Nonlinear least squares is then used to find the value of the complex index of refraction that best fits the theoretical degree of linear polarization, derived using a polarimetric bidirectional reflectance distribution function, to the turbulence-corrected degree of linear polarization. To verify the proposed material-characterization technique, experimental results of two painted metal samples are provided and analyzed.

An extended use of two crossed Babinet compensators as a wavefront sensor for adaptive optics applications is proposed. This method is based on the lateral shearing interferometry technique in two directions. A single record of the fringes in a pupil plane provides the information about the wavefront. The theoretical simulations based on this approach for various atmospheric conditions and other errors of optical surfaces are provided for better understanding of this method. Derivation of the results from a laboratory experiment using simulated atmospheric conditions demonstrates the steps involved in data analysis and wavefront evaluation. It is shown that this method has a higher degree of freedom in terms of subapertures and on the choice of detectors, and can be suitably adopted for real-time wavefront sensing for adaptive optics.

Anisotropic diffusion is widely used for noise reduction. The performance of anisotropic diffusion, in general, depends on the shape of the energy surface. The partial differential equation model is established and analyzed in the continuous domain while is implemented in the discrete domain. Therefore, the anisotropic diffusion bears some fuzziness due to the approximation. We present a novel noise removal algorithm based on fuzzy logic and anisotropic diffusion theory. The experimental results demonstrate that the proposed method has the advantage of maximizing noise reduction and preserving fine details of the images. In addition, the method can enhance the contrast of the images well.

Our study proposes a nonrigid image registration method between different color channels in a color image sequence. It minimizes the entropy in a dominant subspace of the joint distribution of two or more images. The proposed algorithm is based on the observation that the displacement between color channels affects only the dominant subspace in the joint distribution of pixel values. We also propose the use of gradient direction to give extra robustness to our similarity function. Experiments estimating motion parameters for B-spline nonrigid deformation models demonstrate the effectiveness of the proposed registration technique.

We propose a support-vector-machine (SVM) tree to hierarchically learn from domain knowledge represented by low-level features toward automatic classification of sports videos. The proposed SVM tree adopts a binary tree structure to exploit the nature of SVM's binary classification, where each internal node is a single SVM learning unit, and each external node represents the classified output type. Such a SVM tree presents a number of advantages, which include: 1. low computing cost; 2. integrated learning and classification while preserving individual SVM's learning strength; and 3. flexibility in both structure and learning modules, where different numbers of nodes and features can be added to address specific learning requirements, and various learning models can be added as individual nodes, such as neural networks, AdaBoost, hidden Markov models, dynamic Bayesian networks, etc. Experiments support that the proposed SVM tree achieves good performances in sports video classifications.

Statistically based iterative algorithms such as maximum likelihood-expectation maximization (ML-EM) are used for image reconstruction in single photon emission computed tomography (SPECT). Unmatched projector/backprojector pairs are sometimes used to accelerate the iteration process in the reconstruction algorithm. In this work, we propose and explore the use of an unmatched projector/backprojector pair for demultiplexing in multipinhole SPECT. Several simulations are conducted to evaluate the performance of the proposed method with uniform, hot-rod, and cold-rod phantoms. The proposed method incorporates an unmatched backprojector to utilize selective multiplexed projection data in reconstruction algorithms, while the projector is modeled as accurately as possible to represent realistic imaging geometry and the physical effects of multipinhole SPECT. The root mean square (rms) error and backprojection speed are evaluated to determine an unmatched backprojector. Our results demonstrate that the proposed method provides high-quality multipinhole SPECT images without multiplexing-related artifacts when a well-chosen unmatched backprojector is used.

This paper presents a method for registration of noisy airborne images for the purpose of the detection of moving objects. A new iterative algorithm is developed and presented for the correction of geometrical distortion caused by global motion in a scene. A binary hypotheses test is subsequently established using a likelihood ratio test (LRT) to classify the pixels in the corrected image as either locally moving (object motion) or not moving (stationary). The paper also incorporates the use of the Expectation-Maximization method for estimation of statistical image features needed by the LRT. We use and present experiments with real image sequences to validate the analytical developments.

We present a novel Hough transform method for moving point target detection by using a 4-D parameter space. A new representation, which uses four parameters (the distance variable , the angle variable , the velocity variable v, and the distance variable S), is proposed for constant velocity target in the 3-D observation space X-Y-T. By estimating velocity, a target trajectory can be transformed into a 4-D parameter space with a limited range of projection options. Our simulation and analysis show that the new algorithm can produce positive results in suppressing noise points with less computational cost.

Two-dimensional entropic thresholding methods apply gray-level spatial correlation to thresholding and achieve much better performance than 1-D methods, while suffering from large time consumption. To utilize gray-level spatial correlation in thresholding with less time consumption, we define and describe a new entropic thresholding approach employing the gray-level spatial correlation (GLSC) histogram. The GLSC histogram is determined using the gray value of the pixels and the number of their neighboring pixels of similar gray value, which is different from a 2-D histogram. During the entropic criterion function computation, the entropy yielded by different elements in the GLSC histogram is weighted by a nonlinear weighting function, which we suggest. In the experiment, Kapur's 1-D method and three 2-D methods reported by Abutaleb and Sahoo are employed for comparision. Experiments on many real-world images demonstrate that the proposed method yields equivalent or even better results than 2-D ones while saving time remarkably and significantly outperforms Kapur's 1-D method without too much more time consumption generally.

Emotion categorization of natural scene images represents a very useful task for automatic image analysis systems. Psychological experiments have shown that visual information at the emotion level is aggregated according to a set of rules. Hence, we attempt to discover the emotion descriptors based on the composition of visual word representation. First, the composition of visual word representation models each image as a matrix, where elements record the correlations of pairwise visual words. In this way, an image collection is modeled as a third-order tensor. Then we discover the emotion descriptors using a novel affective-probabilistic latent semantic analysis (affective-pLSA) model, which is an extension of the pLSA model, on this tensor representation. Considering that the natural scene image may evoke multiple emotional feelings, emotion categorization is carried out using the multilabel k-nearest-neighbor approach based on emotion descriptors. The proposed approach has been tested on the International Affective Picture System and a collection of social images from the Flickr website. The experimental results have demonstrated the effectiveness of the proposed method for eliciting image emotions.

This paper proposes an advanced fire-flame detection algorithm using camera images for a better performance than conventional sensor-based systems that are limited to a small area. First, candidate flame regions are detected from the captured images using a background model and flame-color model. After forming probability density functions for the intensity variation, wavelet energy, and motion orientation on a time axis, these probability density functions are changed into membership functions for fuzzy logic. Finally, the result function is made by defuzzification, and the probability value of a fire flame is estimated. The proposed algorithm is successfully applied to various fire videos, including indoor and outdoor fires, and shows a better detection performance when compared with other methods.

This paper presents a novel stereo system, based on a graphics processing unit (GPU), for pedestrian detection in real images. The process of obtaining a dense disparity map and the edge properties of the scene to extract a region of interest (ROI) is designed on a GPU for real-time applications. After extracting the histograms of the oriented gradients on the ROIs, a support vector machine classifies them as pedestrian and nonpedestrian types. The system employs the recognition-by-components method, which compensates for the pose and articulation changes of pedestrians. In order to effectively track spatial pedestrian estimates over sequences, subwindows at distinctive parts of human beings are used as measurements for the Kalman filter.

Image corner detection is one of fundamental problems of computer vision and image processing research. Most of the corner detectors detect too much redundant information and increase unnecessary computational costs. We present a new mask that uses only the margin pixels of two circles. To avoid the unnecessary computing, when the mask is scanning areas of similar intensity, the mask will go on with the next nucleus directly. Then a fast corner detection algorithm based on a double circle mask is proposed. We test the performance of our algorithm on digital signal processing and the experimental results show that our new detector performs better and costs less time than the three other methods to which it is compared.

We present two concepts to create multiview 3-D displays with high spatial and angular resolution at a reasonable system cost. We investigate a rear projection approach using only one projector with a digital micromirror device as a light modulator. The first concept is based on time sequentially illuminating the entire light modulator from different directions. Each illumination direction corresponds to a different viewing zone. We design an illumination system that generates all distinct illumination beams, and a lens system integrated into the projection screen to enlarge the viewing zones. A second concept is based on a projection screen architecture that steers images into different horizontal directions and does not require a directional illumination of the light modulator. In this way, the entire acceptance étendue of the projection system can be used for every image. This is achieved by horizontally moving a double-sided lenticular sheet with respect to a sheet of microlenses with a square footprint. Both concepts are investigated with advanced optical simulations.

Light scattering by finite nanostructures is a topic for modern photonics. The scattering can be investigated numerically by performing memory-demanding and long-running computer simulations. When the electromagnetic field inside the nanostructure is quasiperiodic the computations can be thousand times faster. In addition, when the particles in the structure and the distance between the particles is small compared to the incident wavelength, the scattered fields can be calculated even analytically. We study the scattering of light by a photonic cluster made of small particles using quasiperiodicity. The scattered field is calculated analytically and the conditions of the resonance and zero scattering are found. The validity of the obtained results is verified via comparison with the results calculated using the reliable local perturbation method.

The probability-hypothesis-density (PHD) filter as a multitarget recursive Bayes filter has generated substantial interest in the visual tracking field due to its ability to handle a time-varying number of targets. But the target's trajectory cannot be identified within its own framework. To complement the ability of PHD, the auction algorithm is combined to calculate the object trajectories automatically. We present a motion detection, dynamic, and measurement equation, as well as visual multitarget tracking algorithm based on Gaussian mixture probability hypothesis density with trajectory computation in detail. Experimental results on a large video surveillance dataset show that the proposed multitarget tracking framework improves the tracker and recognizes tracks when a variable number of targets appear, merge, split, and disappear, even in cluttered scenes.