The main-to-sidelobe suppression ratio (MSSR) is significant to filters. The tap weight errors worsen the MSSR of the finite impulse response (FIR) microwave photonic filters (MPFs). The MSSR can be improved by shaping the multicarrier optical source spectra with high precision. By compensating the errors with an iteration method, the sidelobes of the amplitude response can be optimized to increase the MSSR. Such a method is simple, effective, and compatible with all FIR MPF approaches. In the experiment, optical spectra of Gaussian profiles were taken as an example, and an MSSR improvement from 50 to 63 dB was demonstrated.

Spatiotemporal motion trajectory can accurately reflect the changes of motion state. Motivated by this observation, this letter proposes a method for key frame extraction based on motion trajectory on the spatiotemporal slice. Different from the well-known motion related methods, the proposed method utilizes the inflexions of the motion trajectory on the spatiotemporal slice of all the moving objects. Experimental results show that although a similar performance is achieved in the single-objective screen, by comparing the proposed method to that achieved with the state-of-the-art methods based on motion energy or acceleration, the proposed method shows a better performance in a multiobjective video.

An avalanche photodiode (APD) fabricated in 0.35  μm high-voltage complementary metal-oxide semiconductor (CMOS) technology, which was originally optimized for linear mode applications, is characterized in Geiger mode operation. This work shows that the used design concept is also suitable for single-photon detection applications and achieves a photon detection efficiency of 22.1% at 785 nm due to a thick detection zone and 3.5 V excess bias. At this operation point, the single-photon APD achieves good results regarding afterpulsing probability (3.4%) and dark count rate (46 kHz) with respect to the large active diameter of 86  μm.

The rear-view image system is one of the active safety devices in cars and is widely applied in all types of vehicles and traffic safety areas. However, studies made by both domestic and foreign researchers were based on a single image capture device while reversing, so a blind area still remained to drivers. Even if multiple cameras were used to expand the visual angle of the car’s rear-view image in some studies, the blind area remained because different source images were not mosaicked together. To acquire an expanded visual angle of a car rear-view image, two charge-coupled device cameras with optical axes angled at 30 deg were mounted below the left and right fenders of a car in three light conditions—sunny outdoors, cloudy outdoors, and an underground garage—to capture rear-view heterologous images of the car. Then these rear-view heterologous images were rapidly registered through the scale invariant feature transform algorithm. Combined with the random sample consensus algorithm, the two heterologous images were finally mosaicked using the linear weighted gradated in-and-out fusion algorithm, and a seamless and visual-angle-expanded rear-view image was acquired. The four-index test results showed that the algorithms can mosaic rear-view images well in the underground garage condition, where the average rate of correct matching was the lowest among the three conditions. The rear-view image mosaic algorithm presented had the best information preservation, the shortest computation time and the most complete preservation of the image detail features compared to the mean value method (MVM) and segmental fusion method (SFM), and it was also able to perform better in real time and provided more comprehensive image details than MVM and SFM. In addition, it had the most complete image preservation from source images among the three algorithms. The method introduced by this paper provided the basis for researching the expansion of the visual angle of a car rear-view image in all-weather conditions.

We propose a method for measuring and quantifying image quality in push-broom hyperspectral cameras in terms of spatial misregistration caused by keystone and variations in the point spread function (PSF) across spectral channels, and image sharpness. The method is suitable for both traditional push-broom hyperspectral cameras where keystone is corrected in hardware and cameras where keystone is corrected in postprocessing, such as resampling and mixel cameras. We show how the measured camera performance can be presented graphically in an intuitive and easy to understand way, comprising both image sharpness and spatial misregistration in the same figure. For the misregistration, we suggest that both the mean standard deviation and the maximum value for each pixel are shown. We also suggest how the method could be expanded to quantify spectral misregistration caused by the smile effect and corresponding PSF variations. Finally, we have measured the performance of two HySpex SWIR 384 cameras using the suggested method. The method appears well suited for assessing camera quality and for comparing the performance of different hyperspectral imagers and could become the future standard for how to measure and quantify the image quality of push-broom hyperspectral cameras.

One of the greatest challenges of representation-based face recognition is that the training samples are usually insufficient. In other words, the training set usually does not include enough samples to show varieties of high-dimensional face images caused by illuminations, facial expressions, and postures. When the test sample is significantly different from the training samples of the same subject, the recognition performance will be sharply reduced. We propose a robust kernel collaborative representation based on virtual samples for face recognition. We think that the virtual training set conveys some reasonable and possible variations of the original training samples. Hence, we design a new object function to more closely match the representation coefficients generated from the original and virtual training sets. In order to further improve the robustness, we implement the corresponding representation-based face recognition in kernel space. It is noteworthy that any kind of virtual training samples can be used in our method. We use noised face images to obtain virtual face samples. The noise can be approximately viewed as a reflection of the varieties of illuminations, facial expressions, and postures. Our work is a simple and feasible way to obtain virtual face samples to impose Gaussian noise (and other types of noise) specifically to the original training samples to obtain possible variations of the original samples. Experimental results on the FERET, Georgia Tech, and ORL face databases show that the proposed method is more robust than two state-of-the-art face recognition methods, such as CRC and Kernel CRC.

An analysis of laser backscattering enhancement is pursued to probe the parameters that affect a laser radar cross-section (LRCS) measurement. The performance of backscattering enhancement is investigated by calculating the LRCS of the conducting targets with a finite size. E-wave polarization is assumed for incident waves in continuous random media. Targets configuration and the beam size in addition to the spatial coherency are those parameters that are studied to clarify their effects on the accuracy of the LRCS compared to the case of a plane wave incidence in a free space and random media.

Electro-optical imaging sensors are widely distributed and used for many different purposes, including civil security and military operations. However, laser irradiation can easily disturb their operational capability. Thus, an adequate protection mechanism for electro-optical sensors against dazzling and damaging is highly desirable. Different protection technologies exist now, but none of them satisfies the operational requirements without any constraints. In order to evaluate the performance of various laser protection measures, we present two different approaches based on triangle orientation discrimination on the one hand and structural similarity on the other hand. For both approaches, image analysis algorithms are applied to images taken of a standard test scene with triangular test patterns which is superimposed by dazzling laser light of various irradiance levels. The evaluation methods are applied to three different sensors: a standard complementary metal oxide semiconductor camera, a high dynamic range camera with a nonlinear response curve, and a sensor hardened against laser dazzling.

Although autostereoscopic display is considered to be mainstream in the three-dimensional (3-D) display market for the near future, practical quality problems still exist due to various challenges such as the accommodation-vergence conflict and crosstalk. A number of studies have shown that these problems reduce the visual comfort and reliability of the perceived workload. We present two experiments for investigating the effect of parallax distribution, which affects the behavior of the accommodation and vergence responses and crosstalk on visual comfort in autostereoscopic display. We measured the subjective visual scores and perceived depth position for watching under various conditions that include foreground parallax, background parallax, and crosstalk levels. The results show that the viewers’ comfort is significantly influenced by parallax distribution that induces a suitable conflict between the accommodation and vergence responses of the human visual system. Moreover, we confirm that crosstalk changes significantly affect visual comfort in parallax barrier autostereoscopic display. Consequently, the results can be used as guidelines to produce or adjust the 3-D image in accordance with the characteristics of parallax barrier autostereoscopic display.

Challenges remain in resolving drug (fluorescent biomarkers) distributions within small animals by fluorescence diffuse optical tomography (FDOT). Principal component analysis (PCA) provides the capability of detecting organs (functional structures) from dynamic FDOT images. However, the resolving performance of PCA may be affected by various experimental factors, e.g., the noise levels in measurement data, the variance in optical properties, the number of acquired frames, and so on. To address the problem, based on a simulation model, we analyze and compare the performance of PCA when applied to three typical sets of experimental conditions (frames number, noise level, and optical properties). The results show that the noise is a critical factor affecting the performance of PCA. When input data containing a low noise (<5%), by a short (e.g., 6 frame) projection sequence, we can resolve the poly(DL-lactic-coglycolic acid)/indocynaine green (PLGA/ICG) distributions in heart and lungs, even though there are great variances in optical properties. In contrast, when 20% Gaussian noise is added to the input data, it hardly resolves the distributions of PLGA/ICG in heart and lungs even though accurate optical properties are used. However, with an increased number of frames, the resolving performance of PCA may gradually recover.

The work that established and explored the links between visual hierarchy and conceptual ontology of firearms for the purpose of threat assessment is continued. The previous study used geometrical information to find a target in the visual hierarchy and through the links with the conceptual ontology to derive high-level information that was used to assess a potential threat. Multiple improvements and new contributions are reported. The theoretical basis of the geometric feature extraction method was improved in terms of accuracy. The sample space used for validations is expanded from 31 to 153 firearms. Thus, a new larger and more accurate sequence of visual hierarchies was generated using a modified Gonzalez’ clustering algorithm. The conceptual ontology is elaborated as well and more links were created between the two kinds of hierarchies (visual and conceptual). The threat assessment equation is refined around ammunition-related properties and uses high-level information from the conceptual hierarchy. The experiments performed on weapons identification and threat assessment showed that our system recognized 100% of the cases if a weapon already belongs to the ontology and in 90.8% of the cases, determined the correct third ancestor (level concept) if the weapon is unknown to the ontology. To validate the accuracy of identification for a very large data set, we calculated the intervals of confidence for our system.

An algorithm for an active protection system with two or more passive infrared sensors based on the principle of triangulation and an extended measurement vector consisting of time-to-go (TTG) estimation is proposed to address high-speed short-range threats. The proposed algorithm exploits the full potential of passive sensors enabling the use of target irradiance in a manner to estimate the TTG along with angle information. The approach here uses target irradiance measured at successive scans to initialize a fixed interval iteration scheme for estimating the TTG. The Newton’s method is used for estimating the TTG, the estimate is then added to the measurement vector and position estimation is performed using an extended Kalman filter. Computer simulations demonstrate the resulting improvement in estimation and feasibility for real-time application of the proposed algorithm.

This paper proposes an adaptive charge sharing (ACS) method for reducing power consumption in liquid crystal displays (LCDs). Our ACS method involves calculating the power consumption of all data lines assuming the charge is shared and analyzing the analog characteristics of the data transitions. With conventional CS, charge is shared between data lines only when the polarities of data signals change. Our ACS method selectively shares charge even when no polarity change occurs, but only if CS provides an overall reduction in power consumption. To compare the performance of ACS and conventional CS, we applied the ACS method to common inversion methods, namely, column, two-dot, and Z inversion. Our simulation results demonstrate that the ACS method can effectively reduce power consumption, especially with the column and Z inversion methods. The average power consumption of the ACS method with column and Z inversion was 87.7% and 84.7%, respectively, of the conventional CS power consumption.

An approach of scale-unambiguous relative pose estimation for space uncooperative targets based on the fusion of low resolution three-dimensional time-of-flight camera and monocular camera is proposed. No a priori knowledge about the targets is assumed. First, a modified range–intensity Markov random field model is presented to quickly reconstruct the range value for each feature point. Second, the scale-ambiguous relative pose estimation algorithm based on extended Kalman filter–unscented Kalman filter–particle filter combination filter is designed in vision simultaneous localization and mapping framework. Third, the overall scale factor estimation approach based on range–intensity fusion image, which takes the feature points’ range reconstruction uncertainty as measurement noise, is proposed for the final scale-unambiguous pose estimation. Finally, some simulations demonstrate the validity and capability of the proposed approach.

This paper presents a part-based human detection method that is invariant to variations in the view of the human and partial occlusion by other objects. First, to address the view variance, parts are extracted from three views: frontal-rear, left profile, and right profile. Then a random set of rectangular parts are extracted from the upper, middle, and lower body as the distribution of Gaussian. Second, an individual part classifier is constructed using random forests across all parts extracted from the three views. From the part locations of each view, part vectors (PVs) are generated and part bases (PB) are also formalized by clustering PVs with their weights of each PB. For testing, a PV for the frontal-rear view is estimated using trained part detectors and is then applied to the trained PB for each view class. Then the distance is computed between the PB and PVs. After applying the same process to the other two views, the final human and its view having the minimum score are selected. The proposed method is applied to pedestrian datasets and its detection precision is, on average, 0.14 higher than related methods, while achieving a faster or comparable processing time with an average of 1.85 s per image.

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and re-enters at a later frame, the re-entering location and variations in rotation, scale, and other three-dimensional orientations of the target are not known, thus complicating the detection and tracking of reappearing targets. A new training-based target detection algorithm has been developed using tuned basis functions (TBFs). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, called clutter rejection module, to determine the target re-entering frame and location of the target. The second algorithm has been designed using the spatial domain correlation-based template matching (TM) technique. If the target re-enters the current frame, the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed TBF-TM-based reappearing target detection algorithm has been tested using real-world forward-looking infrared video sequences.

A self-calibration technique based on genetic algorithms (GAs) with simulated binary crossover (SBX) and laser line imaging is presented. In this technique, the GA determines the vision parameters based on perspective projection geometry. The GA is constructed by means of an objective function, which is deduced from the equations of the laser line projection. To minimize the objective function, the GA performs a recombination of chromosomes through the SBX. This procedure provides the vision parameters, which are represented as chromosomes. The approach of the proposed GA is to achieve calibration and recalibration without external references and physical measurements. Thus, limitations caused by the missing of references are overcome to make self-calibration and three-dimensional (3-D) vision. Therefore, the proposed technique improves the self-calibration obtained by GAs with references. Additionally, 3-D vision is carried out via laser line position and vision parameters. The contribution of the proposed method is elucidated based on the accuracy of the self-calibration, which is performed with GAs.

Multimode service (MMS) systems allow broadcasters to provide multichannel services using a single HD channel. Using these systems, it is possible to provide 3DTV programs that can be watched either in three-dimensional (3-D) or two-dimensional (2-D) modes with backward compatibility. In the MMS system for 3DTV broadcasting using the Advanced Television Systems Committee standards, the left and the right views are encoded using MPEG-2 and H.264, respectively, and then transmitted using a dual HD streaming format. The left view, encoded using MPEG-2, assures 2-D backward compatibility while the right view, encoded using H.264, can be optionally combined with the left view to generate stereoscopic 3-D views. We analyze 2-D and 3-D perceptual quality when using the MMS system by comparing items in the frame-compatible format (top–bottom), which is a conventional transmission scheme for 3-D broadcasting. We performed perceptual 2-D and 3-D video quality evaluation assuming 3DTV programs are encoded using the MMS system and top–bottom format. The results show that MMS systems can be preferable with regard to perceptual 2-D and 3-D quality and backward compatibility.

The nonaxial interferometric position measurement of rotating objects can be performed by imaging the laser beam of the interferometer to a rotating mirror which can be a sphere or a cylinder. This, however, requires such rotating mirrors to be centered on the axis of rotation as a wobble would result in loss of the interference signal. We present a tracking-type interferometer that performs such measurement in a general case where the rotating mirror may wobble on the axis of rotation, or even where the axis of rotation may be translating in space. Aside from tracking, meaning to measure and follow the position of the rotating mirror, the interferometric measurement errors induced by the tracking motion of the interferometer itself are optically compensated, preserving nanometric measurement accuracy. As an example, we show the application of this interferometer in a scanning x-ray tomography instrument.

The traditional phase-shifting profilometry technique is based on the projection of digital interference patterns and computation of the absolute phase map. Recently, a method was proposed that used phase interpolation to the corner detection, at subpixel accuracy in the projector image for improving the camera–projector calibration. We propose a general strategy to improve the accuracy in the search for correspondence that can be used to obtain high precision three-dimensional reconstruction. Experimental results show that our strategy can outperform the precision of the phase-shifting method.

The results of analysis and experimental investigation of a laser goniometer (LG), working in the mode of the noncontact measurement of an object’s angular position, are presented. The important feature of this approach is the very wide range of high-accuracy measurements. In this case, the LG, characterized by the accuracy of ∼0.1 arc sec, has big advantages in comparison to photoelectrical autocollimators which have a rather narrow range of measured angular positions. Our results indicate that the use of a laser dynamic goniometer makes it possible to measure constant angles with an accuracy of 0.05 to 0.1 arc sec in the range of possible angles of 15 to 20 deg. If the measured angle is varying, the residual measurement error contains an additional component, which is equal to ∼0.2 arc sec, induced by the nonflatness of the optical polygon’s faces and by the problems with statistical averaging of the measurement results.

The case of diffraction tomography with limited angle of projections is discussed from the algorithmic and experimental points of view. To reconstruct a three-dimensional distribution of refractive index of a micro-object under study, we use a hybrid approach based on the simultaneous algebraic reconstruction technique (SART) enhanced by a compressed sensing reconstruction technique. It enables us to apply the standard computed tomography algorithms (which assume that the rays are traveling in straight lines through the object) for phase data obtained by means of digital holography. We present the results of analysis of a phantom and real objects obtained by applying SART with anisotropic total variation (ATV) minimization. The real data are acquired from an experimental setup based on a Mach–Zehnder interferometer configuration. Also, it is proven that in the case of simulated data, the limited number of projections captured in a limited angular range can be compensated by a higher number of iterations of the algorithm. We also show that the SART + ATV method applied for experimental data gives better results than the data replenishment algorithm.

We present a shear interferometer that is based on an air wedge placed in the Fourier domain of a 4f-configuration as the shearing element. The two images are formed by the reflections from the front and reverse surfaces of the wedge. Due to a lateral displacement of the reflected beams in the Fourier domain, the interference pattern in the sensor domain is modulated by carrier fringes. Hence, the system is capable of single shot operation. The great advantage of this configuration over already existing shearing setups that make use of air wedges is that the shear can be set independently from the carrier modulation.

Carbon-fiber-reinforced plastic (CFRP) composites are widely used in aerospace and concrete structure reinforcement due to their high strength and light weight. Terahertz (THz) time-domain spectroscopy is an attractive tool for defect inspection in CFRP composites. In order to improve THz nondestructive testing of CFRP composites, we have carried out systematic investigations of THz reflection and transmission properties of CFRP. Unidirectional CFRP composites with different thicknesses are measured with polarization directions 0 deg to 90 deg with respect to the fiber direction, in both reflection and transmission modes. As shown in the experiments, CFRP composites are electrically conducting and therefore exhibit a high THz reflectivity. In addition, CFRP composites have polarization-dependent reflectivity and transmissivity for THz radiation. The reflected THz power in the case of parallel polarization is nearly 1.8 times higher than for perpendicular polarization. At the same time, in the transmission of THz wave, a CFRP acts as a Fabry–Pérot cavity resulting from multiple internal reflections from the CFRP–air interfaces. Moreover, from the measured data, we extract the refractive index and absorption coefficient of CFRP composites in the THz frequency range.

The accuracy of calibration patterns, their fabrication, and their setup are some of the important challenges in a zoom-lens camera calibration process. We address these problems by using a cross-diffractive optical element, which generates a virtual, dense, and robust calibration grid. We show that a 33×33 calibration grid provides enough control points to fill the entire field of view for 10 to 20× zoom lenses. We show that the calibration of a zoom camera at infinity can be done using this method. A polynomial function has been used to model the variation of the intrinsic calibration parameters over the zoom range. The obtained calibration model has also been validated using a well-known target pattern.

Projector nonlinearity is a common problem for digital structured light-based three-dimensional (3-D) shape measurement techniques. A temporal-spatial binary encoding method is presented for the purpose of eluding it. We build a 3-D shape measurement scheme by combining our proposed method with phase measurement profiling. A standard sinusoidal fringe pattern is divided into more than two binary fringe patterns using specially designed temporal and spatial binary encoding rule based on intensity hierarchic quantification, and then are in-focus projected onto the measured object at a time sequence to reconstruct a frame phase-shifting fringe image. On account of the projected binary fringe pattern strictly consisting of zeros and ones, the influence of the projector nonlinearity on the measurement result can be effectively ruled out and simultaneously enables high-quality sinusoidality. In-depth investigations by theoretical analysis and experiments are conducted to demonstrate the performance of this method.

A technique based on a spatial light modulator is proposed for the labeling of nonplanar surfaces. This technique arises from the combination of a general method for generation of digital holograms with a diffractive axilens. Unlike existing methods in which hologram contrast critically decreases out of the focal plane, our proposed approach allows the system to increase the focus depth, resulting in enhanced hologram images out of the focal plane. Two existing methods for hologram generation are theoretically and experimentally compared in terms of efficiency and contrast: the iterative Fourier transform algorithm-based method and the random multiplexing of different lenses method. The most suitable one is selected for the implementation of the new axilens-based technique. Experimental results obtained with the axilens method provide a significant enhancement of the image quality of holograms obtained out of the focal plane when compared with an existing technique. The approach proposed in this manuscript may be of interest in industrial applications, where alphanumeric data must be registered on nonflat surfaces, as in the cases of beverage cans or bottles.

Secondary optics that allow for the integration of a light-emitting diode (LED)-based luminescent light source into various étendue-limited applications—such as projection systems—are investigated. Using both simulations and experiments, we have shown that the optical efficacy of the luminescent light source can be increased using a collimator. A thorough analysis of the influence of the collimator’s refractive index on the optical outcoupling and luminance is investigated and it is shown that it is most optimal to use a refractive index of 1.5. The optimal shape of the collimator is equal to that of a compound parabolic concentrator. Experimental results show that by using a collimator, we can improve the amount of outcoupled light with a factor of 1.8 up to 2.1 depending on the used optical configuration of the LED-based luminescent light source.

A porous-core circular photonic crystal fiber is designed for low-loss terahertz (THz) wave propagation. The circular arrangement of air holes, both in the periodic cladding and the porous core, makes it possible to guide most of the optical power through low-loss air, which is confirmed by the rigorous analysis of modal properties of the fiber while maintaining the single-mode propagation condition. The simulation results, found by using an efficient finite element method, show that a flattened dispersion of ±0.09  ps/THz/cm within 0.9 to 1.3 THz and an ultra-low material loss of 0.053  cm−¹ at f=1  THz is obtained for the reported design at optimal parameters. This kind of structure can be fabricated using capillary stacking or a sol–gel technique and is expected to be useful for wideband imaging and telecom applications.