This PDF file contains the editorial “Fortune Tellers, Optical Engineering, World Events, and the Future” for OE Vol. 50 Issue 05

The propagation of laser beam in a flow aligned nematic liquid crystal (NLC) and its interaction with liquid are illustrated in this letter. The effect of polarization and scattering on the transmitted power through the NLC under external perturbation flow is demonstrated here. It is found that the flow rate has a significant role in the modulation of refractive index of the medium leading to scattering and change in polarization.

Point-and-shoot, TV studio broadcast, and thermal infrared imaging cameras have significantly different applications. A parameter that applies to all imaging systems is Fλ/d, where F is the focal ratio, λ is the wavelength, and d is the detector size. Fλ/d uniquely defines the shape of the camera modulation transfer function. When Fλ/d<2, aliased signal corrupts the imagery. Mathematically, the worst case analysis assumes that the scene contains all spatial frequencies with equal amplitudes. This quantifies the potential for aliasing and is called the spurious response. Digital data cannot be seen; it resides in a computer. Cathode ray tubes, flat panel displays, and printers convert the data into an analog format and are called reconstruction filters. The human visual system is an additional reconstruction filter. Different displays and variable viewing distance affect the perceived image quality. Simulated imagery illustrates different Fλ/d ratios, displays, and sampling artifacts. Since the human visual system is primarily sensitive to intensity variations, aliasing (a spatial frequency phenomenon) is not considered bothersome in most situations.

Supporting an unconstrained user interface is an important issue in iris recognition. Various methods try to remove the constraint of the iris being placed close to the camera, including portal-based and pan-tilt-zoom (PTZ)-based solutions. Generally speaking, a PTZ-based system has two cameras: one scene camera and one iris camera. The scene camera detects the eye's location and passes this information to the iris camera. The iris camera captures a high-resolution image of the person's iris. Existing PTZ-based systems are divided into separate types and parallel types, according to how the scene camera and iris camera combine. This paper proposes a novel PTZ-based iris recognition system, in which the iris camera and the scene camera are combined in a coaxial optical structure. The two cameras are placed together orthogonally and a cold mirror is inserted between them, such that the optical axes of the two cameras become coincident. Due to the coaxial optical structure, the proposed system does not need the optical axis displacement-related compensation required in parallel-type systems. Experimental results show that the coaxial type can acquire an iris image more quickly and accurately than a parallel type when the stand-off distance is between 1.0 and 1.5 m.

A novel array configuration composed of multiple concentric circles is proposed for sparse aperture imaging systems. To get better image quality, one property of the modulation transfer function, called the practical resolution limit, is chosen as the optimization criterion. The optimized novel array configurations with aperture numbers of 6, 7, 9, 10, and 12 are given by using the simulated annealing algorithm. The comparisons of modulation transfer function with Golay and circle arrays with an equivalent sub-aperture number are implemented. Results show that the optimized arrays have smaller practical resolution limit than other array configurations with relative continuous and uniform coverage in the frequency plane.

This paper presents a tomograph for small animal fluorescence imaging. The compact and cost-effective system described in this article was designed to address the problem of tumor detection inside highly absorbent heterogeneous organs, such as lungs. To validate the tomograph's ability to detect cancerous nodules inside lungs, in vivo tumor growth was studied on seven cancerous mice bearing murine mammary tumors marked with Alexa Fluor 700. They were successively imaged 10, 12, and 14 days after the primary tumor implantation. The fluorescence maps were compared over this time period. As expected, the reconstructed fluorescence increases with the tumor growth stage.

Reconstructing the integral of a distribution of radioactivity along a line from Compton camera data could be used to produce a parallel projection, or to perform tomosynthesis, or to reconstruct the whole three-dimensional distribution itself. Analytic methods for reconstructing an integral of radioactivity along a line are presented here. The sets of data that allow an integral along a line and a parallel projection of the distribution to be reconstructed are determined here by interpreting these methods from a geometric viewpoint. These methods and the sets of data depend upon which of the two models is assumed for the data. Both of these models have been previously proposed by other researchers. In addition, a new camera design is proposed here that makes it possible to measure all these sets of data. In this design, a first detector element has to be seen from the second detector in only a "semicircle of direction." Also, two techniques for increasing the sensitivity of the new camera design are proposed here. Computer simulations are performed to illustrate these reconstruction methods.

In this study, a beat signal recalibration method was developed for optical coherence tomography (OCT) with a high-speed wavelength-swept source. By adopting a voltage-controlled oscillator (VCO) modulated by a sinusoidal waveform as a trigger for the OCT system, the broadening of the beat frequency due to laser tuning rate variations was recalibrated. For this study, OCT based on a Fourier domain mode-locked (FDML) laser at a sweep rate of 60.9 kHz was demonstrated. OCT images of 1500×409 pixels were obtained with the sensitivity of 100 dB. Temporal frequency variations in the FDML laser and OCT images obtained with the proposed technique were also described. When compared to a conventional recalibration method using optical components, swept source optical coherence tomography operated with a VCO clock exhibited superior performance and high stability. From the experimental results, it was demonstrated that the proposed method is sufficient to recalibrate the time-frequency variations in interferometry with a high-speed wavelength-swept source.

The broadband imaging capabilities of a vanadium oxide microbolometer camera were investigated in the far-infrared for applications in real-time terahertz imaging and analysis. To accomplish this, we used an optical configuration consisting of a broadband terahertz source, terahertz filtering optics, and a modified commercial broadband microbolometer camera. A blackbody radiator was employed as the broadband terahertz source to illuminate the microbolometer array with all components in a nitrogen purged enclosure. Data was taken using several different levels of radiant flux intensity. Optical filtering were necessary to isolate incident radiation frequencies into a band from 1.5 to 7.5 THz. Fourier transform infrared spectroscopy was used to characterize the transmission properties of each optical component. The noise equivalent differential temperature (NEDT) and the noise equivalent power (NEP) were recorded over a range of blackbody intensities. We discuss the relative utility of these two figures of merit for terahertz imaging. For example, at a blackbody temperature of 925°C the NEDT was recorded below 800 mK, and the NEP was calculated to be 136 pW/√Hz. This study provides a complete analysis of a microbolometer as the detector component of a terahertz imaging system in a broadband imaging configuration.

A low-budget surface slope-measuring instrument, the developmental long-trace profiler (DLTP), was recently brought into operation at the Advanced Light Source Optical Metrology Laboratory. The instrument is based on a precisely calibrated autocollimator and a movable pentaprism. The capability of the DLTP to achieve submicroradian surface slope metrology has been verified via cross-comparison measurements to other high-performance slope-measuring instruments when measuring the same high-quality test optics. Further improvement of the DLTP is achieved by replacing the existing bulk pentaprism with a specially designed mirror-based pentaprism, which offers the possibility to eliminate systematic errors introduced by inhomogeneity of the optical material and fabrication imperfections of a bulk pentaprism. We provide the details of the mirror-based pentaprism design and describe an original experimental procedure for precision mutual alignment of the mirrors. The algorithm of the alignment procedure and its efficiency are verified with rigorous ray-tracing simulations. Results of measurements of a spherically curved test mirror and a flat test mirror using the original bulk pentaprism are compared to measurements using the new mirror-based pentaprism, demonstrating the improved performance.

We present a comprehensive derivation of the so-called diffuse to near-normal-viewing reflectance factor of an architectural paint coating and its measurement with an integrating sphere. We focus our attention to the surface correction terms and consider the case when the surface is rough. We point out limits of the standard formula with the so-called Saunderson corrections commonly used for paint coatings. We provide and discuss a corrected definition of the roughness-dependent "gloss factor" needed to describe specular-component excluded measurements. We show that as the roughness of the surface increases, the specular-excluded reflectance-factor increases, approaching its value with the specular-component included.

We propose a high-speed surface profiler using a modified Fourier transform profilometry (FTP) approach. Our system geometry is different from a conventional profiler in that the fringe-projection lens and the imaging lens are at different heights from a reference plane. FTP computer simulation and experimental data are provided that supports our theoretical development. Our profiler provides a 1σ rms error of about 4 μm for an integrated circuit chip sample in an area of 14 mm × 6.5 mm with a 0.13 second data acquisition time. It is shown that our theoretical derivation is suitable for a micrometer scale object measurement.

An alternative method to determine particle position in 3D is herewith proposed. The procedure to be followed is simple since it avoids a complicated experimental set-up and several computation steps to obtain the final particle position. In order to compute the position and radius of a particle image, the continuous wavelet and Hough transforms are employed: the proposed method is based on the size and position calculation for a particle diffraction image central spot size. The size and centroid of the central spot size render the z and x-y position of a particle image, respectively. This approach has been applied to simulated and experimental particle images. Simulated particle images have been obtained using the near field Lorenz-Mie theory, and show between the actual and calculated central spot size. An average relative error of 0.4% and 1.7% for x-y and z directions, respectively, was found in the analysis. The extraction of the 3D particle position was done with experimental particle images obtained from particle motion provoked by heated water inside a channel. The quality of the particle images determines the accuracy of the calculation of its central spot size.

Surfaces that are recovered by integrating slope estimates are prone to errors caused by discontinuities in the surface. We propose combining laser sectioning and photometric stereo (PS) to estimate surface shape. PS is used to estimate slope; laser lines are used to measure four height profiles. The slopes are integrated along paths that start from the laser height profiles and avoid discontinuities. The scheme is shown to mitigate the bias and surface discontinuity problems associated with PS.

This paper describes a new peak detecting algorithm combined Carré phase shifting interferometry with white light interferometry. The new method can carry the fast, accurate, and noncontact measurements. The testing system employs a Mirau objective on a piezoelectric transducer based on a Zeiss microscope. Several numerical simulations are first carried to analyze its phase calculation errors due to the visibility variation in the white light correlogram. Afterwards, the centroid method is adopted to concentrate the phase extraction on the zero-order fringe, which not only decreases the phase error, but also frees the data processing from the phase unwrapping procedure. The capabilities of the system and the proposed algorithm are evaluated through the measurements of a microresonator and two standard step heights. In the measurement of the 44-nm standard step height, no overshoot shows up on or close to the edge of the sample. At last, three different methods include: white light phase shifting interferometry, phase shifting interferometry and white light interferometry are employed to make a comparison on the measurement precision.

A choice of methods exists for determining the variability of an averaged wavefront measurement. Pixel-by-pixel standard deviation (SD) maps provide a spatial description of the variability as well as a scalar magnitude. An efficient algorithm for computing SD maps as measurements occur is given. Results for simulated and experimental wave-front maps are shown. Plots of the average SD as a measurement progresses can be used to characterize a test system and determine the minimum number of measurements required for acceptable results.

An improved conjugate gradient algorithm (ICGA) is presented to inverted particle size distribution (PSD) with ensemble light scattering methods. The narrow unimodal, broad unimodal, or the multipeak modal PSD can be inverted from diffraction data with ICGA. In the algorithm, a convergence threshold should be changed according to the particle size distribution width (PSDW). However, we cannot always know the PSDW beforehand, thus we propose to calculate the PSDW by the light-scattering data. Afterward, we can select the convergence threshold. We experimented on some samples and their mixture. The results show the proposed method can be applied to inverted PSD with different distribution models. The resulting errors on the above samples are within 4.55%. The mixture of some particulate certified reference materials can be discerned distinctly, thus the resulting resolutions are acceptable.

Calibration of 3-D optical sensors often involves the use of calibration artifacts consisting of geometric features, such as 2 or more planes or spheres of known separation. In order to reduce data processing time and minimize user input during calibration, the respective features of the calibration artifact need to be automatically detected and labeled from the measured point clouds. The Hough transform (HT), which is a well-known method for line detection based on foot-of-normal parameterization, has been extended to plane detection in 3-D space. However, the typically sparse intermediate 3-D Hough accumulator space leads to excessive memory storage requirements. A 3-D HT method based on voting in an optimized sparse 3-D matrix model and efficient peak detection in Hough space is described. An alternative 1-D HT is also investigated for rapid detection of nominally parallel planes. Examples of the performance of these methods using simulated and experimental shape data are presented.

Currently, the mainstream autostereoscopic displays have a shortcoming: the insufficient brightness. It causes bad influence on the using of autostereoscopic displays. To improve the brightness, a new design method of the backlight module is needed. In this article, one high-brightness light emitting diode (LED) is used, and the light is concentrated to the eyes of observer by using a Fresnel lens and many cylindrical lenses. The brightness is improved significantly. When the user position changes greatly, another LED is lighted up to replace the former. Imitation and experimental results indicate that this method is feasible. Compare with previous backlight modules, this backlight module is brighter and need less electrical energy, and is more suitable for cockpits.

We present a switchable liquid crystal cylindrical lens array fabricated with a combination of a sparse electrode array of multiwall carbon nanotubes (MWCNTs) grown upon a silicon substrate, and a second glass substrate featuring an in-plane switching (IPS) electrode structure. A cylindrical shape of an electric field profile was produced between the MWCNT substrate and the IPS substrate. This cylindrical shape was controlled by the application of an external electric field. The average focal lengths at different voltages were calculated. This adaptive lenticular lens array can be used in autostereoscopic displays.

The reflective spectrum of fiber Bragg gratings (FBGs) might be regarded as the spatial Fourier transform (FT) of the refractive index modulation when the reflection is low. Therefore, the normalized amplitude and the phase which are obtained from the inverse FT of the expected reflection shape are the significant factors for designing the intensity and phase modulation of the index change, respectively. By carefully incorporating and designing the intensity and the phase modulations, we obtain FBGs with arbitrary reflective spectra including cosine/sine, triangle, sawtooth, trapezia and upside-down triangle shapes. Simulation results based on the piecewise uniform method further confirm the proposed method. Such FBGs can easily find their applications in signal generation, parameter demodulation, and so on.

Recently the fiber and the disk laser have been developed as advanced high power lasers of continuous wave type. Their beams are fiber-guided. Their low beam parameter product determines the focused beam as a high power density tool for laser materials processing. The lateral and axial power density distribution is crucial for the process. The measurement of a focused Yb:fiber laser beam is compared with its theoretical profile. While a Gauss beam describes the real beam in the far field, in the vicinity of the focus the beam is similar to a top-hat profile. In particular, the peak power density is lower around the focus than for a Gaussian beam. This provides a flatter, less varying optical tool along a certain axial range. A suitable model of the focused laser beam is achieved by superposition of a Gauss beam with a second but negative Gauss beam, each with matched parameters for power, spot diameter, and Rayleigh length. Owing to its much better accuracy with less than a 20% error, the model beam is applicable, e.g., for simulation of the welding process.

We report on the calibration results of the wavelength of the lasers used in commercial laser interferometers, including the vacuum wavelength deviation from its nominal value, the vacuum wavelength stability, the repeatability of stabilized wavelength, and the secular change of these properties, by analyzing the calibration data accumulated for more than two decades. We present an experimental method of calibrating the frequency of laser interferometers. We also propose a proper time interval and an appropriate uncertainty expression for the vacuum wavelength calibration of the laser interferometers.

Femtosecond laser induced two-photon polymerization has the advantages of high resolution and capability of true three-dimensional (3D) fabrication. In this work, a phase filter-based super-resolution technique was adopted to reduce the size of focus spot in order to achieve exceeded diffraction limit fabrication resolution. The principle of phase modulation of a femtosecond laser was introduced, the parameters of the phase filter were optimized using a genetic algorithm, and then a 3D super-resolution annular phase filter was fabricated. Experimental results proved that the aspect ratio as well as the axial and radial sizes of solidified units was compressed by the optimized phase filter. A maximum aspect ratio compression ratio of 20.8% was achieved. The radial compression ratio of the modulated spot decreased with the increase of laser exposure amount, while the axial compression ratio and aspect ratio compression ratio increased.

A multilongitudinal mode fiber ring laser sensor is proposed and experimentally demonstrated by measuring the strain applied on the laser sensor head. The ring cavity of the laser is formed by a 3-dB coupler, a section of erbium-doped fiber, and one fiber Bragg grating. Photonic generation of beat signals and strain measurement theory are discussed in detail. The strain applied on the fiber ring cavity is obtained by measuring the beat frequency shift. The selection way of the optimal beat signal for strain measurement is obtained by experimental research and discussion. The root-mean-square deviation of the strain and the response of beat frequency to the strain are 2.7 μɛ and 1.5 kHz/μɛ at 1993 MHz, respectively. The proposed sensor scheme offers a cost-effective and high-stability device for strain measurement.

A microdisplacement sensor formed by a fixed and mobile hole-array based slot photonic crystal (slot-PhC) components is demonstrated. The sensing technique is based on a nanoscale cavity with a high-Q factor in photonic crystals (PhCs). The high-Q nanocavity (H0-cavity) is formed by only laterally shifting two adjacent holes outwards slightly in the opposite direction. The properties of the microdisplacement sensor are analyzed theoretically and simulated using the finite-difference time-domain method. The simulation results indicate that with a proper operating frequency, a quasilinear measurement of microdisplacement is achieved with a sensitivity of 1.0a⁻¹ (a is the lattice constant) in the sensing range between 0.00a and 0.20a. Although other researchers such as Xu et al.¹ who demonstrated a micro displacement sensor possessing an equivalent sensitivity, the Q factor is only 40. In this paper, combined with harmonic analysis, we show numerically that an intrinsic Q value of up to 6×10³ is achieved. In addition, it is worth mentioning that when the parameters of the H0-cavity are determined, the resonant frequency of the H0-cavity remains approximately constant as the mobile PhC segment shifts along the common axis. It will be easier and more accurate for measurements in practical applications.

A 32×32 pixel array has been fabricated in a 0.35-μm complementary metal-oxide semiconductor process with the aim of producing two-dimensional laser Doppler blood-flow images. In the design, each pixel contains five basic elements: a photodiode, a front-end consisting of a current to voltage converter, voltage amplifier, antialiasing filter, and buffer. The analog design is optimized for the detection of laser Doppler blood-flow signals and thus offers advantages over conventional sensors. The analog outputs are passed through an on-chip multiplexer and digitized by an external analog-to-digital converter. The sensor has been fully characterized electrically and optically using modulated electrical and optical signals. A calibration process for fixed pattern noise reduces the standard deviation of the ac gain by a factor of 2. The imaging response is tested by imaging a vibrating test structure and a rotating diffuser. Blood-flow measurements on a finger before and after occlusion demonstrate that the sensor array is capable of detecting blood-flow signals from tissue. The knowledge gained from the characterization of the design can be used to develop a fully integrated laser Doppler blood-flow sensors with a higher number of pixels.

A simple low-cost technique for the fabrication of portable optical oxygen sensors is described. The sensing film is based on the oxygen sensing dye tris(4,7-diphenyl-1,10-phenanthroline)ruthenium(II) {[Ru(dpp)3]²⁺} and dye-entrapped core-shell silica nanoparticles embedded in a sol-gel matrix. The feasibility of coating a photodiode with the oxygen sensing film to fabricate a portable optical sensing device is investigated. The sensitivity of the sensor is quantified in terms of the ratio IN2/IO2, where IN2 and IO2 represent the detected fluorescence intensities in pure nitrogen and pure oxygen environments, respectively. The experimental result reveals that the portable optical oxygen sensor has sensitivity of 41. The sensor exhibits a linear response for oxygen concentrations in the range 0 to 60%. A preparation procedure for coating photodiodes with the oxygen film that produces repetitive and reliable sensing devices is proposed. The developed optical oxygen sensor is portable, low-cost, highly sensitive, and lacks optical filter elements. The proposed sensor is a cost-effective alternative to traditional electrochemical-based oxygen sensors and provides a platform for other optically based sensors.

An adaptive modified two-dimensional time-spreading/wavelength-group-hopping embedded M-sequence code (TS/WGH embedded M-sequence code) is proposed for enhancing the cardinality, confidentiality, and bit error rate (BER) of synchronous networks. The proposed arrayed-waveguide-grating (AWG)-based modified TS/WGH embedded M-sequence encoder/decoder (codecs) is constructed by using a fine AWG to generate an M-sequence code pattern and then using multiple-coarse AWGs to spread this pattern in the wavelength domain. The signals produced by the coarse AWGs are then spread in the time domain using optical delay lines. In addition, an algorithm based on an anticipative-warning-time mechanism and a degree of weighted load balance (DWLB) policy is proposed for changing the signature address code word of each user on a sufficiently frequent basis in order to thwart synchronous-network attacks by eavesdroppers. Overall, the simulation results show that, compared to conventional two-dimensional prime-hop code (PHC) and modified PHC and previous TS/group-hopping embedded M-sequence code, the proposed adaptive modified TS/WGH embedded M-sequence code proposed in this study yields an effective reduction in the multiple-access interference and BER while simultaneously improving the degree of confidentiality.

Generation of chaos from acousto-optic (A-O)Bragg cell modulators with an electronic feedback has been studied for over 3 decades. Since an acousto-optic Bragg cell with zeroth- and first-order feedback exhibits chaotic behavior past the threshold for bistability, such a system was recently examined for possible chaotic encryption of simple messages (such as a low-amplitude sinusoidal signal) applied via the bias input of the sound cell driver. Subsequent recovery of the message signal was carried out via a heterodyne-type strategy employing a locally generated chaotic carrier, with threshold parameters matched to the transmitting Bragg cell. In this paper, we present numerical results and detailed interpretations for signal encryption and recovery under hybrid A-O electronic feedback using a heterodyne strategy. Important features of this setup, such as the system robustness in terms of parameter matching (feedback gain, dc bias, and time delay) are also examined in some detail.

We report on a generalization of the eigenfunction expansion method to model the performance of multichannel optical-fiber communications systems in the presence of nonlinear phase noise. Our method is fast, accurate, and easy to implement for numerical simulations in multichannel wavelength-division multiplexed (WDM) systems. We also account for the dispersion to all orders for increased accuracy in multichannel systems.

In measuring form deviation of gear tooth flanks by laser interferometry, the collected interference fringe pattern (IFP) is badly distorted, in the case of shape, relative to the actual tooth flank. Meanwhile, a clear and definite mapping relationship between the collected IFP and the actual tooth flank is indispensable for both transforming phase differences into deviation values and positioning the measurement result on the actual tooth flank. In order to solve these problems, this paper proposes a method using the simulation tooth image as a bridge connecting the actual tooth flank and the collected IFP. The mapping relationship between the simulation tooth image and the actual tooth flank has been obtained by ray tracing methods [Fang et al., Appl. Opt. 49(33), 6409-6415 (2010)]. This paper mainly discusses how to build the relationship between the simulation tooth image and the collected IFP by using a matching algorithm of two characteristic point sets. With the combination of the two above-mentioned assistant mapping relationships, the mapping relationship between the collected IFP and the actual tooth flank can be built; the collected IFP can be positioned on the actual tooth flank. Finally, the proposed method is employed in a measurement of the form deviation of a gear tooth flank and the result proves the feasibility of the proposed method.

Computer-generated holograms (CGHs) allow to transfer the high 2D-positioning accuracy of modern lithography equipment into high precision 3D-shape measurements, e.g. in CGH asphere metrology. In this contribution, we give a detailed look into the characterization of steep topologies with CGHs on the example of a 90 deg axicon surface, requiring rather high line densities in the hologram. Several aspects gain importance with increasing CGH line densities when measuring dimensional quantities such as the cone angle of the surface: misalignment of the setup, fabrication effects of the CGH rigorous effects of the high density grating, and effects due to wavelength variations of the interferometer. This paper presents the experimental approach for the cone angle measurement and a systematic analysis of its measurement uncertainty, focusing on the specifics of this null test CGH measurement.

A new iterative method for creating a pure phase hologram to diffract light into two arbitrary two-dimensional intensity profiles in two output planes is presented. This new method combines the Gerchberg-Saxton (GS) iterative algorithm and the compensation iterative algorithm. Numerical simulation indicates that the new method outperforms the most frequently used method in accuracy when it is used to generate large size images. A preliminary experiment of optical reconstruction has been taken and used to verify the feasibility of our method.

This paper proposes a single-field deinterlacing method based on the autoregressive model and edge map. The new method interpolates missing pixels through estimating the deinterlaced covariance from the interlaced covariance, instead of estimating the edge orientations as previous intrafield deinterlaced methods (line average, edge-based line-average, direction-oriented interpolation, etc.) do. The proposed method adopts autoregressive mechanism, which considers mutual influence between the estimated missing pixels in a slip window. In addition, adding an edge map in our algorithm is used to reduce the computational complexity. The experimental results show that the proposed method outperformed the previous method in peak signal-to-noise ratio, and common artifacts (serration, line crawl, flicker, blurring, etc.) are significantly reduced.

Image interpolation addresses the problem of obtaining high resolution (HR) images from its low resolution (LR) counterparts. For observed LR images with aliasing artifacts caused by undersampling, commonly used interpolation methods cannot recover HR images well, and may often interpolate over-fitting artifacts. In this paper, based on the observation that natural images normally have redundant similar patches, a new patch-synthesis-based interpolation method is proposed for image interpolation. In the proposed method, an inference method based on Markov chain is adopted to select the best patches from the input LR image and synthesize them into the undersampled areas of a desired HR image. In order to improve the efficiency of the algorithm, we also introduce fields of experts to model the sparse prior knowledge and use it to measure the compatibilities among neighboring patches. Experimental results compared with traditional interpolation methods demonstrate that our method cannot only alleviate the aliasing artifact, but also produce better results in terms of quantitative evaluation and subjective visual quality

In this paper, an adaptive color transform for image compression is introduced. In each block of the image, coefficients of the color transform are determined from the previously compressed neighboring blocks using weighted sums of the RGB pixel values, making the transform block-specific. There is no need to transmit or store the transform coefficients because they are estimated from previous blocks. The compression efficiency of the transform is demonstrated using the JPEG image coding scheme. In general, the suggested transformation results in better peak signal-to-noise ratio (PSNR) values for a given compression level.

Recently, a category of watermarking techniques based on binary phase-only filter (BPOF) has been proposed for image authentication. In such techniques, the authentication is implemented by evaluating the correlation between Fourier phase information and the hidden watermark bitplane. In this paper, we reveal the security flaws of BPOF-based watermarking algorithms and propose sophisticated tampering attacks against them. We show how the attacker can easily tamper with a watermarked image without being detected. Experimental results demonstrate that our attacks are successful in tampering watermarked images. The watermarking schemes are proven to be fundamentally flawed.

A new full-parameter singular value decomposition-based image quality assessment (IQA) method, which aims at capturing the loss of structural content instead of measuring the distortion of pixel intensity value, is proposed. Both the singular vectors and the singular value are considered as features and weight for quantifying major information, respectively, to evaluate the distortion degree in images. Extensive validation experiments are conducted with two kinds of test images, one of which is the LIVE database supplied by the University of Texas and the other is created from our own simulation. The prediction performance of the presented metrics, such as accuracy, monotonicity, and consistency, is measured. The experiment results show that, compared to several state-of-the-art image quality metrics, the performance of the proposed IQA is in better alignment with the perception of the human visual system in predicting image quality, particularly when comparing images containing different types of distortions.

Along with the improvement of image watermarking techniques, the necessity for effectively and comprehensively evaluating various algorithms becomes imperative. In this paper, we first propose a new categorization that fits for most of the existing watermarking algorithms that work in the wavelet domain. Then an adaptive watermarking attack for evaluating the robustness of watermarking schemes that are based on the proposed categorization is presented. This attack determines the flat regions, edges, and textures of the watermarked image and based on known features of each region the proposed attack tries to destroy the watermark information. This is done by separately manipulating the wavelet coefficients of each region such that the least visual distortion will be imposed on the attacked image. We study some recent watermarking techniques in terms of the watermark invisibility and robustness through subjective experiments and objective metrics. The average peak signal-to-noise ratio (PSNR) of the watermarked image after applying the proposed attack is more than 35 dB and the average normalized cross correlation (NC) for the extracted watermark is lower than 0.4, so theoretically, the watermark is not detectable. Moreover, the proposed method does not consider any knowledge about the underlying watermarking algorithm.

A novel edge based method for detecting a salient object in an image is proposed. The core idea of our work is that the problem of detecting a salient object is transformed to the problem of finding closed curves in the edge map. It requires only edge detection and "closed curve" detection. The novelty lies in two aspects: first, when producing an edge map, the number of edge pixels is limited to make sure that edges detected in the background are relatively little; second, when detecting a salient object from an edge map, the contour of the salient object is detected in a simple way to decrease the effect of edges in the background. Experiments conducted on Liu et al.'s [Proc. CVPR, pp. 1-8, Minneapolis, MN (2007)] dataset of 5000 images show that the method is comparable with several popular methods from literature.

This paper proposes a novel saliency model using multiple region-based features. The original image is initially segmented into a set of regions using the mean shift algorithm, and region merging is performed to obtain a moderate segmentation result. Then, three types of regional saliency measures are calculated using region-based features including local/global color difference, orientation difference, and spatial distribution, and they are integrated into an overall regional saliency measure for each region. Finally, the pixel-wise saliency map is generated by combining regional saliency measures with the distance-weighted color similarity between each pixel and each region. Experimental results demonstrate that our saliency model achieves an overall better saliency detection performance than previous saliency models, and the saliency maps generated using our model are more suitable for content-based applications such as salient object detection, content-aware image retargeting, and object-based image retrieval.

Automatic target detection is an important application in the hyperspectral image processing field. Most statistics-based detection algorithms use second-order statistics to construct detectors. However, for target detection in a real hyperspectral image, targets of interest usually occupy a few pixels with small population. In this case, high-order statistics could characterize targets more effectively than second-order statistics. Also, the inherent variation of spectra of targets is an obstacle to successful target detection. In this paper, we propose a regularized high-order matched filter (RHF) which uses high-order statistics to build an objective function and uses a regularized term to make the algorithm robust to target spectral variation. A gradient descent method is used to solve this optimization problem, and we obtain the convergence properties of the RHF. According to the experimental hyperspectral data, the results have shown that the proposed algorithm performed better than those classical second-order statistics-based algorithms and some kernel-based methods.

This paper describes a novel feature representation and selection approach for classification problems, especially for visual object detection within the framework of AdaBoost. This work is distinguished by two contributions. The first contribution is the introduction of a new feature generation and representation method called the spatial dependence matrix feature, which not only provides information related to the first-order statistics distribution of the object, but also gives some information about the relative positions within the object, more importantly, it can provide different degrees of importance for different discriminative parts within the object. It is flexible, extendable, and compatible with Haar-like features. The second contribution is an improved feature selection algorithm, which introduces a novel weighted features redundancy elimination rule that eliminates the irrelevant and redundant features from the candidate feature pool at every boosting stage when gradually training detector, and thus two advantages can be obtained: leading to selecting features with more discrimination and the final detector having a higher accuracy, and also increasing the learning convergence and achieving high training rates. Extensive experiments with synthetic and real scene data sets show that our works outperform conventional AdaBoost and are better than or at least equivalent to previously published results.

In order to efficiently enhance the dark nighttime videos, the high-quality daytime information of the same scene is often introduced to help the enhancement. However, due to camera motion, the introduced daytime may not have exactly the same scene of the nighttime videos. Thus, the final fused moving objects may not produce reasonable results. In this paper, we make the following two contributions: 1. we propose a global motion estimation-based scheme to address the problem of scene differences between daytime and nighttime videos. 2. Based on this, we further propose an improved framework for nighttime video enhancement which can efficiently recover the unreasonable enhancement results due to scene differences. Experimental results show the effectiveness of the proposed algorithm.

Computational color constancy algorithms play a key role in achieving desired color reproduction in digital cameras. Failure to estimate illumination chromaticity correctly will result in invalid overall colour cast in the image that will be easily detected by human observers. A new algorithm is presented for computational color constancy. Low computational complexity and low memory requirement make the algorithm suitable for resource-limited camera devices, such as consumer digital cameras and camera phones. Operation of the algorithm relies on characterization of the range of possible illumination chromaticities in terms of camera sensor response. The fact that only illumination chromaticity is characterized instead of the full color gamut, for example, increases robustness against variations in sensor characteristics and against failure of diagonal model of illumination change. Multiple databases are used in order to demonstrate the good performance of the algorithm in comparison to the state-of-the-art color constancy algorithms.

In this paper, we propose a stable illumination change adaptive tracking algorithm in which the color model update and the target localization are mutually constrained to each other. The mutual constraint is the result of sharing the same five-dimensional feature space, where the feature vector is composed of the three color components and the x,y coordinates of pixels inside the target region. The use of the five-dimensional feature vector introduces spatiality in the color model update, i.e., the re-clustering of the feature space is constrained by the spatial location of the pixels corresponding to the target color. The spatial constraint on the color model update is also due to the use of a window which contains the pixels used in the color model update, where the location of the window is decided by the current target location. The color model update is performed by a five-dimensional mean shift-based clustering algorithm. The update in the color components in the five-dimensional feature vector handles the illumination change in the colors in the target region. The five-dimensional mean shift-based clustering updates also the x,y coordinates in the five-dimensional vector, and thus constrains the target localization. The target localization uses the x,y coordinates of the mean vectors of the five-dimensional vectors corresponding to each color bin. The target location is computed as a minimizer of a proposed energy functional, which is proposed such that the relative spatial locations of the mean vectors are considered in the target localization. The mutual constraint of the color model update and the target localization makes the tracking stable under various situations such as global illumination change, partial occlusion, and cluttered background. It can stably track the target even in the appearance of major background colors that are also major colors of the target object.

The speckle reduction is an important problem in coherent imaging, such as synthetic aperture radar or ultrasound imagery. Speckle is a nonadditive and nonwhite process, and the reduction of speckle without blurring sharp features is known to be difficult. We present a new speckle reduction algorithm that utilizes an anisotropic directional filter that adapts to the proximity and direction of nearest important features. To remove speckle without blurring important features, the locations and direction of edges in the image are estimated. Then for each pixel in the image, the distance and angle to the nearest edge are computed by an efficient algorithm and stored in distance and angle maps. Finally, for each pixel, an anisotropic directional filter aligned to the nearest edge is applied. The shape and the orientation of the filter are determined from the distance and the angle maps. The new speckle reduction algorithm is tested with both synthesized and real synthetic aperture radar images. The performance of the new algorithm is also compared to those of earlier speckle reduction approaches. We show that the new algorithm performs favorably compared to other speckle reduction algorithms in reducing speckle without blurring important features.

This paper proposes a robust detection and tracking method that can detect and track ship targets in cluttered forward looking infrared image sequences. The proposed method includes two major steps, target detection and target tracking. Because the target's imaging size will be scaled-up gradually along with the imaging distance being reduced, the target's imaging process is analyzed in detail and the target's imaging size is estimated in real-time. Based on the estimation of the target's imaging size, the targets with different imaging sizes can be treated as small targets by image scaling operation and detected successfully using the improved multilevel filter and iterative segmentation technique. In the tracking stage, the histogram back-projection technique, which has little effect on the movement of the camera, is applied to the mean shift procedure for real-time application. Extensive experiments demonstrate the utility and the performance of the proposed approach.

Finger-vein recognition uses the finger-vein pattern extracted from the captured vein images to identify individuals. However, the captured vein images contain irregular shading and noise. To extract effective vein pattern from these unclear images, this paper proposes a novel vein pattern extraction approach by running the region growing operator on the different seeds. As the proposed method emphasizes continuity and symmetry of valleys in the cross-sectional profile, it can extract the robust finger-vein patterns and be against irregular shading and noise. Experimental results show that the proposed method achieves robust vein pattern extraction and provides a lower equal error rate in finger-vein recognition.

The principle and system structure of the depth measurement of weld pool surface in tungsten insert gas (TIG) welding are first introduced in the paper, then the problem of the common phase lines is studied. We analyze the causes and characteristics of the phase lines, and propose a phase correction method based on line ratio. The paper presents the principle and detail processing steps of this phase correction algorithm, and then the effectiveness and processing characteristics of the algorithm are verified by simulation. Finally, the algorithm is applied to phase processing in the depth measurement of the TIG weld pool surface and obtains satisfying results.

In this paper, we propose a framework for image classification. An image is represented by multiple feature channels which are computed by the bag-of-words model and organized in a spatial pyramid. The main difference among feature channels resides in what type of base descriptor in the bag-of-words model is extracted. The overall features achieve different levels of the trade-off between discriminative power and invariance. Support vector machines with kernels based on histogram intersection distance and χ² distance are used to obtain a posteriori probabilities of the image in each feature channel. Then, four data fusion strategies are proposed to combine intermediate results from multiple feature channels. Experimental results show that almost all the proposed strategies can significantly improve the classification accuracy as compared with the single cue methods and, especially, prod-max performs best in all experiments. The framework appears to be general and capable of handling diverse classification problems due to the multiple-feature-channel-based representation. Also, it is demonstrated that the proposed method achieves higher, or comparable, classification accuracies with less computational cost as compared with other multiple cue methods on challenging benchmark datasets.

We investigate the generation and transformation of Bessel beams through linear and nonlinear optical crystals. We outline the generation of high-order vortices due to propagation of Bessel beams along the optical axis of uniaxial crystals and expand this to the nonlinear regime by outlining a new phase-matching process (full conical phase matching) in second harmonic generation of vector Bessel beams for various symmetries in uniaxial crystals. We demonstrate the principles experimentally in a uniaxial BBO crystal and find excellent agreement between the experimental and theoretical results. The results imply a coupling of the intrinsic and extrinsic optical angular momentum of the resulting fields, which may have importance in studies involving quantum entanglement of the angular momentum basis of light.

This PDF file contains the errata for “OE Vol. 50 Issue 05 Paper OE ERR-MAY2011-1” for OE Vol. 50 Issue 05

This PDF file contains the errata for “OE Vol. 50 Issue 05 Paper OE ERR-MAY2011-2” for OE Vol. 50 Issue 05