This PDF file contains the editorial “Grooving on Technology” for OE Vol. 43 Issue 10

We present a beam-shaping technique to enhance emitting power density for a high-power laser-diode array stack. By use of a stripe mirror and a high-reflection mirror, the laser source height of 42 mm is folded to 21 mm and the emitting power density is increased to 365 W/cm² from a raw emitting power density of 194 W/cm². Moreover, the beam parameter product (BPP) that is used to evaluate the beam quality is effectively improved to 168-mm mrad from a raw BPP of 336-mm mrad in the fast axis for the collimated high-power laser-diode array stack.

Lateral-pressure tuning of a coaxially embedded fiber Bragg grating in a cylindrical polymeric package is demonstrated. The polymeric coating, having very low stiffness and high Poisson's ratio, enables effective transfer of the applied radial load to the axial direction. Such a transfer enhances the tuning range and reduces birefringence. A tuning range more than 1 nm, with negligible bandpass broadening and peak splitting, could be demonstrated. A lateral pressure sensitivity of 0.3 nm/(N/mm), which is almost 7 times as high as that of bare FBG, could be obtained.

A scheme for wavelength and polarization insensitive all-optical clock extraction and enhancement of nonreturn-to-zero (NRZ) data is proposed and demonstrated. At 10 Gbit/s, more than 7-dB clock enhancement and 19-dB clock-to-data suppression ratio (CDSR) enhancement have been realized using a semiconductor optical amplifier (SOA) and a reflective fiber Bragg grating (FBG) over a 30-nm input wavelength range.

The wavelength of light affects the working distance to the beam waist and the mode field diameter in a spherical-end fiber lens. The compensation effects of the chromatic aberration in the fiber lens are shown, and the predicted results are found to be in good agreement with the experimental values.

A compact fiber variable optical attenuator (VOA) with <1-dB insertion loss and >25-dB dynamic range is proposed and demonstrated at the 1550-nm band using a fiber collimator lens and a bulk-micromachined deformable micromirror. Three versatile VOA designs are presented that exploit the principle of 3-D beam spoiling to achieve broadband polarization insensitive attenuation using simple single-drive controls.

Based on near-infrared spectral absorption and fiber-optic sensor technology, an experimental setup for low-water-content measurement of crude oil is developed. The advantages of this method include fast measurement, high accuracy, keeping the measured oil free of pollution, and being suitable for long-term on-line continuous monitoring. This technology can be used for those applications that require high-quality water-in-oil measurement and process control. The measurement resolution for water content is better than 0.005% in the range from zero to 2% by volume. Measurement errors are estimated to be ±0.01% in the range from zero to 1%.

Laser scanner angular resolution greatly depends on both the spatial sampling interval and laser beamwidth, though often the former is emphasized and the latter overlooked. Given the widespread use of 3-D laser scanners, a rigorous metric that unifies both factors is necessary to accurately model system resolution. A new resolution measure that incorporates both sampling and beamwidth is derived using an ensemble average linear system theory. Analysis of two commercially available scanning systems demonstrates the need for the new measure.

Fast and accurate methods for Raman amplifier propagation equations are proposed. Numerical results demonstrate that these methods can increase the accuracy by more than one or two orders of magnitude in comparison with the classical methods, and the computing speed can increase more than 16 times compared to the classical fourth-order Runge-Kutta method on the same conditions.

This PDF file contains the editorial “Optics and Photonics for Homeland Security” for OE Vol. 43 Issue 10

We present a compact optical decryption system using the generalized phase contrast (GPC) method implemented in a planar integrated micro-optical (PO) device. An encrypted phase pattern is deciphered by the application of a decrypting phase key and visualized using a miniaturized implementation of the GPC method. The current proof-of-principle demonstration makes use of a PO device composed of diffractive micro-optical elements to form a 4-f lens imaging setup with a spatial phase-only filter at the Fourier plane. Successful decryption of a 17×9-pixel encrypted phase mask is achieved with high-contrast visualization of the original pattern.

An encryption method of a 3-D object based on the phase modulation of an object wave is proposed. The phase of the object wave is modulated by a virtual optical random phase mask using a digital holographic technique. The keys of an encryption step are both a phase distribution and a position of the virtual optical phase mask. If either of them is not correct, we cannot decrypt the 3-D object. Owing to a characteristic of a hologram, we can see some parallax of a reconstructed 3-D object. Experimental results are presented to confirm the proposed method.

We present the results of applying data compression techniques to encrypted three-dimensional objects. The objects are captured using phase-shift digital holography and encrypted using a random phase mask in the Fresnel domain. Lossy quantization is combined with lossless coding techniques to quantify compression ratios. Lossless compression alone applied to the encrypted holographic data achieves compression ratios lower than 1.05. When combined with quantization and an integer encoding scheme, this rises to between 12 and 65 (depending on the hologram chosen and the method of measuring compression ratio), with good decryption and reconstruction quality. Our techniques are suitable for a range of secure three-dimensional object storage and transmission applications.

A number of methods have been recently proposed in the literature for the encryption of 2-D information using optical systems based on linear transforms, i.e., the Fourier (FT), the fractional Fourier (FRT), the Fresnel (FST), and the linear canonical transform (LCT). We propose and examine two encryption schemes using the Fresnel transform (FST) based on the use of random phase screens and random jigsaw transforms (JT). The strength and robustness of the level of encryption of the various techniques are examined with respect to blind decryption. These systems are compared with similar FRT- and LCT-based methods. Optical implementations are also discussed and sampling conditions are investigated in the context of the space-bandwidth product.

A method for decrypting a binary phase-only mask using an amplitude-only spatial light modulator key is proposed. The system is based on a double passage through a generalized phase contrast setup. A binary amplitude key is converted to phase for decrypting a binary phase-only encrypted pattern on the first passage. The decrypted phase pattern is subsequently converted to an intensity pattern on the second passage. A compact dual-path system, applicable in reflection geometry, is suggested for this decryption operation.

We present a 2-D barcode technique that can be used to authenticate documents. The proposed system holds much more information than one-dimensional barcode. It is robust against different types of noises and distortions. We use double phase encoding to encode information into the 2-D binary barcode. As a result, the technique is secure against unauthorized detection. We present analysis for the system performance using the statistical properties of double-phase encoding. The algorithm is tested under several types of noise and distortions, for example, additive noise, geometric distortion, fading, scratches, and occlusion. We compare the performance of amplitude-based double phase encoding and fully phase double phase encoding with that of an ordinary 2-D barcode with error-correcting code. Computer simulations and optical experiments are presented to test the robustness of the proposed method.

The performance of a fully phase-based encryption system is analyzed. The encryption is done using a double random fractional Fourier domain random phase encoding technique. The input amplitude data to be encrypted are binary text and a grayscale image of Lena. We study the tolerance to data loss and binarization of the encrypted data/image. The effects of noise perturbations on the encrypted data are also studied. To evaluate the quality of the recovered image, the mean-square error is used as a metric to compare the recovered image with the original input image. Results of computer simulation are presented for analysis.

A special NIST database of live-scan fingerprints with elastic distortion was prepared. It is used to evaluate the effect of elastic and other distortions on correlation filters. The need for normalized and finely or coarsely rotationally aligned data is addressed, and performance gains for various cases noted.

We address the problem of detecting vehicle targets on the ground by means of an autonomous polarimetric sensor on board a high-altitude air- or spaceborne platform. We studied a sensor system that incorporates a micropolarizer array, a microscanner, and digital signal processors that host algorithms for detecting small targets. These algorithms use statistical techniques to fuse a target's Stokes-vector infrared signature measurements. Fusion is achieved by constructing the joint statistical measures for the target's polarization states. Those states are expressed in terms of the intensity, the percentage of linear polarization, and the angle of the polarization plane. The performance of the sensor system on synthetic polarimetric infrared imagery was evaluated. Relatively good detection and low false-alarm probabilities were achieved even when the number of pixels on targets is as small as four. This is the first report of the development and evaluation of automatic detection in polarimetric imagery containing targets subtending only a small number of pixels.

The recognition of an object in a scene is a common and important task of electronic imaging arising in many defense and security applications. When the image of the sought object is significantly distorted, and the image of the scene is cluttered, noisy, and contains many objects, the commonly used methods based on correlation and comparison of the feature vectors of the images can show poor performance. The approach utilizing the particular model of the hybrid evolutionary algorithm based on image response analysis is proposed to solve the object recognition problem formulated as the global optimization problem. The computational experiments with two-dimensional grayscale images show that the proposed approach can solve complex object recognition problems. It is able to discriminate between objects having a high degree of similarity, and to detect the sought object in the large cluttered and multi-object scene.

Differential absorption radiometers (DARs) using uncooled detectors are introduced as a simple method for low-cost remote sensing of chemical vapors for domestic security. A DAR consisting of a pair of uncooled LiTaO₃ pyroelectric detectors integrated with bandpass filters selected to detect methanol, a simulant of many hazardous vapors, was demonstrated. At a signal-to-noise ratio (SNR) 5, the measured detection limit for methanol was 0.014 atm cm. This corresponds to a detection limit of 5.70×10^–4 atm cm (31.5 mg m^–2) for dimethyl methylphosphonate (DMMP). For comparison, a DAR consisting of a pair of cryogenically cooled HgCdTe (MCT) detectors was also tested. The detector-limited noise equivalent temperature differential (NETD) of the MCT detectors was measured to be 0.38 mK, whereas for the pyroelectric detector it was 115 mK. Despite the much lower detector noise, the MCT-based DAR provided a detection limit of only 0.005 atm cm for methanol, corresponding to 2.04×10^–4 atm cm (11.25 mg m^–2) for DMMP. The relatively poor sensitivity of the MCT-based DAR was shown to be limited by small temperature gradients of 15 mK across the noncoincident fields of view of the detectors in the DAR and by environmental fluctuations, which contributed a total NETD = 37 mK.

A beam-steering system consisting of three cemented achromatic doublets is presented. Intended for use in IR countermeasure applications, our system is designed to operate over the 2- to 5-μm spectrum with minimum angular dispersion. We show that dispersion can be minimized by using doublet lenses fashioned from AMTIR-1 and germanium. Our system is designed to be compact and lightweight, with no internal foci, while allowing steering to ±22.5 deg. We also maintain a minimum 2-in. clear aperture for all steering angles, and a nominal divergence of 1 mrad. Plane wave and Gaussian beam analyses of our system are presented.

The internal reflection of the multimode-interference (MMI)-type device is calculated with the bidirectional beam propagation method. The calculated results indicate that the difference of the effective refractive indices between the core region and the surrounding region has a determining effect on the internal reflection of the MMI-type device. The output taper for the MMI-type combiner and splitter has a more evident effect on the internal reflection than the input taper. The internal reflection decreases with increasing the end width of the taper. For the MMI-type device with appropriate tapers, the internal reflection does not show evident degradation with the deviation of the length of the MMI region from its optimal value.

The bidirectional reflectance distribution function (BRDF) is an important surface property, commonly used to describe reflected light patterns. However, the BRDF is a complex function since it has four angular degrees of freedom and also depends on the wavelength. The direct use of BRDF data set may be inefficient for scene modeling algorithms, for example. Thus, models provide compression and additional functionalities like interpolation. One common way consists in fitting an analytical model to the measurements data set using an optimization technique. But this approach is usually restricted to a specific class of surfaces, to a limited angular or spectral range, and the modeling quality may strongly depend on the optimization algorithm chosen. Moreover, analytical models are unable to actually handle the BRDF dependence on wavelength. We present a new numerical model for acquired spectral BRDF to overcome these drawbacks. This model is based on a separation between the spectral and the geometrical aspects of the BRDF, each of them projected into the appropriate wavelet space. After a brief introduction to the BRDF, the advantages of wavelets and the construction of the model are explained. Then, the performances of modeling are presented and discussed for a large collection of measured and synthetic BRDF data sets. Finally, the robustness of the model is tested with synthetic noisy BRDF data.

We present an algorithm for image reconstruction from data acquired by use of an asymmetric fan-beam configuration with a spatially varying focal length. This algorithm is a natural generalization of our previous algorithm for fan-beam computed tomography (CT) that involves shift-variant filtering, and it possesses desirable noise and numerical properties similar to those in the previous algorithm. We performed computer simulation studies to validate and evaluate the proposed algorithm, and quantitative results demonstrate that the proposed algorithm possesses desirable noise and numerical properties. The filtered backprojection algorithm can reconstruct images from data acquired in a configuration with a constant focal length. In this situation, the proposed algorithm yields images with lower and more uniform noise properties than the filtered backprojection algorithm.

An adjacent sequence iteration method for designing a diffractive element with function of controlling wavefront propagation is presented, and a binary optical element for focusing a diode laser beam in a long focal depth is designed with this method, fabricated by means of photolithography and ion-etching techniques. The simulation calculated with the designed element indicates that the design is successful, and the experiment results of long focal depth by testing the produced element are consistent with the design requirements.

Due to the polarization sensitivity of Raman gain and the random nature of polarization mode dispersion (PMD) in the fiber, the gain of a fiber Raman amplifier (FRA) fluctuates over a wide range during a relatively long time. In this work, a numerical method of obtaining the probability distribution function of the random fluctuating Raman gain in a bidirectionally pumped FRA is presented for the first time, based on the vector theory of stimulated Raman scattering (SRS). After optimizing a bidirectionally pumped FRA to achieve the best tradeoff between an optical signal-to-noise ratio (OSNR) and nonlinear distortions, the proposed method is applied to study the impact of gain fluctuations. The results show that the fluctuations reach their peaks at two values of PMD parameters (D_p), respectively, when D_p is increased from zero. The heights of the two peaks are proportional to the power allocations for the forward and backward pumps, respectively. The results are useful for avoiding high gain fluctuations when bidirectional pumping is applied.

A novel fiber Bragg grating temperature sensor is proposed and experimentally demonstrated with a long-period grating as a linear response edge filter to convert wavelength into intensity-encoded information for interrogation. The sensor is embedded into an aluminum substrate with a larger coefficient of thermal expansion to enhance its temperature sensitivity. A large dynamic range of 110 °C and a high resolution of 0.02 °C are obtained in the experiments. The technique can be used for multiplexed measurements with one broadband source and one long-period grating, and therefore is low cost.

We define a new concept of bisymmetry for multibank wavelets. By extending the theory of multiresolution analysis to multibank wavelets, this work also focuses on the study of four-bank compactly supported bisymmetric orthonormal wavelets. Investigations have shown that there is a class of four-bank compactly supported orthonormal wavelets with bisymmetry, in which any wavelet system can be determined uniquely by its low-pass filter. Thus, the least restrictive conditions are needed for forming a wavelet, so that the free degrees can be reserved for application requirements. Also, such wavelet classes can be parameterized. Therefore, the optimal four-bank wavelets with bisymmetry can be found in this class. Some concrete examples with high vanishing moments are also given. These wavelets can avoid prefiltering, process the boundary conveniently, and enjoy the highly efficient computations in application.

One goal of image processing is to recreate the human visual perception of the original scene. We offer a method of color image enhancement for realistic image display. The algorithm is based on a special implementation of the feed-forward ON-OFF shunting neural network. The properties of the neural network for image processing are first investigated. The computational simulations make clear the strengths and weaknesses of the neural network. Combined with a brightness-based tone reproduction operator, a multiscale extension to the neural network is developed to correct the original version's weaknesses and provides a coherent framework for color image enhancement. The algorithm achieves both dynamic range compression and vivid color rendition and qualitatively approaches the aspects of early visual perception. Extensive tests demonstrate that this method could produce satisfying images without any unexpected results.

Background subtraction is an important issue for achieving effective foreground object detection in video surveillance. Background subtraction requires the timely updating of a background model to gradual illumination changes as well as the significant changes in the background. It is also essential that foreground objects have little impact on the updating of the background. Based on our change-type categories, we propose an adaptive background subtraction method where a two-strategy-based background maintenance is introduced to adapt to different types of changes by using feedback from change segmentation and region classification. The work mainly contributes to the following issues: 1. propose a change segmentation method that detects change regions as well as provides spatiotemporal information about the changes by using fuzzy techniques; 2. propose a fuzzy reasoning method to classify background and foreground changes at the object level; and 3. propose a new method for adaptive background maintenance based on the feedback from pixel-level to object-level processing that is able to avoid tradeoff in the updating rate. Experiments on indoor and outdoor video scenes are conducted and results show that the proposed method adapts well to various background changes without absorbing foreground objects. Comparisons with an existing method using a constant learning rate show an improved performance.

In JPEG image compression algorithms, an entropy coder encodes an end-of-block (EOB) marker for each discrete cosine transform (DCT) block. The well-known Huffman coder encodes one such marker for each block. However, the binary arithmetic coder, which provides greater compression but is not as well known, encodes several EOB tests, one after each nonzero ac coefficient of the block. We present a modification to the JPEG arithmetic coding algorithm to reduce the number of EOB tests. Our algorithm encodes two extra zero ac coefficients for a small percentage of blocks, but it encodes fewer EOB tests. As a result, we reduce the total image code size by about 1.4% on average. In this process, we also study the effectiveness of the DCT and statistical models of this coder.

An acoustic method for the measurement of the effective temperature and refractive index of air for precision length interferometry is described. The method can be used to improve the accuracy of interferometric length measurements outside the best laboratory conditions and also in industrial conditions. The method is based on the measurement of speed of 50-kHz ultrasound over the same distance measured with a laser interferometer. The measured speed of ultrasound is used to define the effective temperature or the refractive index of air along the laser beam path using the equations presented. The measured speed of sound, Cramer equation, dispersion correction, and Edlén equations are used in the fitting of new equations for the effective air temperature and refractive index of air as a function of speed of 50-kHz ultrasound. The standard uncertainties of the effective temperature and the refractive index of air equations are 15 mK and 1.7×10^–8, respectively. The uncertainties of the effective temperature and refractive index of air measured with the test setup for distances of about 5 m are 25 mK and 2.6×10^–8, respectively.

Decreasing feature sizes due to advances in nanotechnology place a premium on careful treatment of phase, length, and time in optics. All three quantities are intermeshed due to morphology at the nanometer length scale. After examining the characteristics of the responses of columnar thin films and chiral sculptured thin films to optical pulses and beams, we put forward the thesis that nanotechnology for optics is a phase-length-time sandwich.

We investigate an optical vector network analysis technique based on optical single-sideband modulation that can provide spectral characterization of optical components in terms of amplitude and phase shift with femtometer wavelength resolution. The fundamentals of the system are analyzed and a mathematical model for the measurement process is derived. Using this model and experimental results, the potential of the technique in terms of frequency resolution is demonstrated. However, it is also found that the measurement accuracy relies on a high suppression of the residual sideband in the optical single-sideband modulation deployed.

A novel wavelength-tunable add-drop multiplexer (ADM) using fiber Fabry-Pérot tunable filters (FFP-TFs) for the bidirectional wavelength division multiplexing (WDM) network is proposed and demonstrated. The wide tuning range, low loss, and low polarization dependence properties of the FFP-TFs are used for the ADM operation. The experimental results show that the wavelength tuning range of this wavelength-tunable ADM can be up to 40 nm. The bit-error-rate performance of the dropped and pass-through channels for a 2.5 Gbit/s system shows the feasibility of ADM.

Evaluation results and an autoalignment method for an optical head of a near-field recoding (NFR) system are presented. The focusing unit is an optical head of a NFR system and is composed of a solid immersion lens (SIL) and an objective lens (OL). Generally, the size of the focusing unit is smaller than that of the conventional optical recording head. Hence there are difficulties in assembling the small focusing unit precisely and a novel method for an effective assembly is required. We compose an evaluation system with an interferometer and evaluate some focusing unit samples aligned and assembled manually and present the obtained results. We also propose a conceptual method of autoalignment to assemble the focusing unit well by a pattern recognition using a neural network. Using the conventional optical tool, Code V, a tolerance analysis of the assembly error between the SIL and the objective lens and an interference pattern analysis for the assembly error are executed. Then, through an analysis of the simulation results, the autoalignment methodology using a neural network approach is proposed.

We investigate the use of low-cost infrared (IR) sensors for the simultaneous extraction of geometry and surface properties of commonly encountered features or targets in indoor environments, such as planes, corners, and edges. The intensity measurements obtained from such sensors are highly dependent on the location, geometry, and surface properties of the reflecting target in a way that cannot be represented by a simple analytical relationship, therefore complicating the localization and recognition process. We propose the use of angular intensity scans and present an algorithm to process them to determine the geometry and the surface type of the target and estimate its position. The method is verified experimentally with planes, 90-deg corners, and 90-deg edges covered with aluminum, white cloth, and Styrofoam packaging material. An average correct classification rate of 80% of both geometry and surface over all target types is achieved and targets are localized within absolute range and azimuth errors of 1.5 cm and 1.1 deg, respectively. Taken separately, the geometry and surface type of targets can be correctly classified with rates of 99 and 81%, respectively, which shows that the geometrical properties of the targets are more distinctive than their surface properties, and surface determination is the limiting factor. The method demonstrated shows that simple IR sensors, when coupled with appropriate processing, can be used to extract substantially more information than that for which such devices are commonly employed.

A linear 128-photosensor array in a complimentary metal-oxide semiconductor (CMOS) standard technology is presented. The characteristics of the pixels are high voltage at the output in the range of 0 to 3.5 V and a pixel memory with the possibility of multiple readouts without significant degradation of information. The ASIC also includes a selection logic to select the pixel to be read. Using this CMOS photodetector array, we also present a low-cost prototype for the distance measurement and 3-D reconstruction of near and small objects, where the optical triangulation method used is appropriate. Good acquisition results are obtained in the experimental test.

The thermal effects of diode-end-pumped Nd:YVO₄ and Nd:YAG lasers are analyzed by a 2-D analytical model and a 3-D numerical model, respectively. The characteristics of the Nd:YVO₄ and Nd:YAG rods are comparatively discussed, including temperature distributions and thermal lensing effects. The model quantitatively separates the end effect from the index parts. Under the same pump configuration, we find that the temperature increase in the Nd:YVO₄ laser was 2 times larger than those in the Nd:YAG laser, while the thermal lensing coefficient of Nd:YAG was 27% higher than that of Nd:YVO₄. We also conclude that a good roundness of the Nd:YVO₄ laser beam profile is expected because nearly symmetric thermal lensing in the a and c axes is predicted from our modeling and measurement. Correspondingly, we perform experiments that are in good agreement with theoretical modeling for the thermal lensing of diode-pumped Nd:YVO₄ and Nd:YAG lasers.

We expand conventional superresolving imaging systems toward extraction of suboptical wavelength structures. An imaging system that is capable of imaging subwavelength details is presented. Homogeneous waves carrying information on spatial frequencies exceeding the classical limit of resolution can be created by diffraction of evanescent waves. These homogeneous waves are able to pass through an imaging system. The high spatial frequencies can be recovered from these homogeneous waves by appropriate decoding. We present the theory of subwavelength structure imaging, depict a special holographic recording method that is eventually implemented in experimental validation in which subwavelengths details are imaged using a conventional imaging setup.

Reliable real-time surface inspection of extended surfaces with high resolution is needed in several industrial applications. With respect to an efficient application to extended technical components such as aircraft or automotive parts, the inspection system has to perform a robust measurement with a ratio between depth resolution and lateral extension of less than 10^–6. This ratio is at least 1 order beyond the solutions that are offered by existing technologies. The concept of scaled topometry consists of a systematic combination of different optical measurement techniques with overlapping ranges of resolution systematically to receive characteristic surface information with the required accuracy. In such a surface inspection system, an active algorithm combines measurements on several scales of resolution and distinguishes between local fault-indicating structures with different extensions and global geometric properties. The first part of this active algorithm finds indications of critical surface areas in the data of every measurement and separates them into different categories. The second part analyzes the detected structures in the data with respect to their resolution, and decides whether a further local measurement with a higher resolution has to be performed. The third part positions the sensors and starts the refined measurements. The fourth part finally integrates the measured local dataset into the overall data mesh. We have constructed a laboratory setup capable of measuring surfaces with extensions up to 1500×1000×500 mm³ (in x, y, and z directions, respectively). Using this measurement system we are able to separate the fault-indicating structures on the surface from the global shape, and to classify the detected structures according to their extensions and characteristic shapes simultaneously. The level of fault-detection probability is applicable by input parameter control.

We report the design of a vertical cavity surface emitting laser (VCSEL) focusing module, suitable for barcode scanning applications. The dimensions of the plastic lens housing are precisely controlled to set the distance between the laser and the focusing lens, without the need of alignment. Measurement results of prototype devices are also reported.