Accepted papers to appear in an upcoming issue
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Calculating corner singularities by boundary integral equations
Shi Hualiang, Ya Yan Lu, and Qiang Du
Doc ID: 282821 Received 14 Dec 2016; Accepted 25 Apr 2017; Posted 26 Apr 2017 View: PDF
Abstract: Accurate numerical solutions for electromagnetic fields near sharp corners and edges are important for nanophotonics applications that rely on strong near-fields to enhance light-matter interactions. For cylindrical structures, the singularity exponents of electromagnetic fields near sharp edges can be solved analytically, but in general the actual fields can only be calculated numerically. In this paper, we use a boundary integral equation method to compute electromagnetic fields near sharp edges, and construct the leading terms in asymptotic expansions based on numerical solutions. Our integral equations are formulated for rescaled unknown functions to avoid unbounded field components, and are discretized with a graded mesh and properly chosen quadrature schemes. The numerically found singularity exponents agree well with the exact values in all the test cases presented here, indicating that the numerical solutions are accurate.
Propagation properties of partially coherent Lorentz beam in uniaxial crystal orthogonal to the optical axis
Dajun Liu, Hongming Yin, guiqiu wang, and Yaochuan Wang
Doc ID: 291232 Received 22 Mar 2017; Accepted 24 Apr 2017; Posted 26 Apr 2017 View: PDF
Abstract: The cross-spectral density function of a partially coherent Lorentz beam propagating in uniaxial crystal orthogonal to the optical axis is obtained, the evolution properties and the spectral degree of coherence for a partially coherent Lorentz beam in uniaxial crystal are illustrated by using numerical examples. The influences of coherence length and the ratio of refractive index ne/no on the normalized intensity and spectral degree of coherence for partially coherent Lorentz beam are analyzed in details.
Deterministic mode representation of random stationary media for scattering problems
Jia Li and Olga Korotkova
Doc ID: 285303 Received 01 Feb 2017; Accepted 23 Apr 2017; Posted 26 Apr 2017 View: PDF
Abstract: Deterministic Mode Representation (DMR) is introduced for a three-dimensional random medium withstatistically stationary refractive index distribution. The DMR allows for designing and fine tuning of novel randommedia via adjustment of the weights of individual deterministic modes. To illustrate its usefulness we have appliedthe decomposition to the problem of weak light scattering from a Gaussian Schell-model medium. In particular, wehave shown how individual deterministic modes of the medium contribute to the scattered far-field spectraldensity distribution.
Local receptive field constrained stacked sparse autoencoder for classification of hyperspectral images
Xiaoqing Wan and Chunhui Zhao
Doc ID: 285752 Received 26 Jan 2017; Accepted 20 Apr 2017; Posted 25 Apr 2017 View: PDF
Abstract: As a competitive machine learning algorithm, stacked sparse autoencoder (SSA) has achieved outstanding popularity in exploiting high-level features for classification of hyperspectral image (HSI). In general, in the SSA architecture, the nodes between adjacent layers are fully connected and they need to be iteratively fine-tuned during pre-training stage, however, the nodes of previous layer further away are less likely to have a dense correlation to the central node of subsequent layer. Therefore, to reduce the classification error and increase the learning rate, this paper proposes the general framework of locally connected SSA, that is, the biologically inspired local receptive field (LRF) constrained deep learning network is employed to characterize the local correlation of spectral features and extract high-level feature representations of hyperspectral data, simultaneously. In addition, the appropriate receptive field centers are concurrently determined by measuring the spatial distances from the neighbor nodes to the central node. Finally, the efficient random forest classifier is cascaded to the last hidden layer of SSA as benchmark classifier. Experimental results on two real HSI data sets demonstrate that the proposed hierarchical LBF constrained SSARF (LRF-SSARF) is superior to state-of-the-art methods in terms of classification accuracy, and it shows much lower training time compared with the result provided by similar SSARF based methodology.
An airplane wing deformation and flight flutter detection method by using 3D speckle image correlation technology
Jun Wu, Zhijing Yu, Tao Wang, Jingchang Zhuge, Yue Ji, and Bin Xue
Doc ID: 286074 Received 02 Feb 2017; Accepted 19 Apr 2017; Posted 25 Apr 2017 View: PDF
Abstract: Airplane wing deformation is an important element of aerodynamic characteristics, structure design, and fatigue analysis for aircraft manufacturing, as well as a main test content of certification about flutter for airplane. This paper presents a novel real-time detection method for wing deformation and flight flutter detection by using 3D speckle image correlation technology. Speckle patterns whose positions are determined through the vibration characteristic of aircraft are coated on the wing, then the speckle patterns are imaged by CCD cameras which are mounted inside aircraft cabin. In order to reduce the computation, a matching technique based on GSI coded points combining the classical epiplolar constraint is proposed, and a displacement vector map for aircraft wing can be obtained through comparing the coordinates of spackle points before and after deformation. Finally, a verification experiment using an aircraft wing model demonstrates the effectiveness and accuracy of the proposed method.
Nonreciprocal waveguiding structures for THz region based on InSb
Pavel Kwiecien, Ivan Richter, Vladimir Kuzmiak, and Jiri Ctyroky
Doc ID: 281546 Received 24 Nov 2016; Accepted 18 Apr 2017; Posted 20 Apr 2017 View: PDF
Abstract: We have studied theoretically and numerically surface magnetoplasmons in three types of THz guiding structures, namely InSb/dielectric planar boundary, InSb/air/metal planar waveguide, and symmetric InSb/air/InSb planar waveguide, in the presence of an external magnetic field. We consider the Voigt magnetooptic configuration in which these structures provide a frequency range where only one propagation direction is allowed to support one-way propagation of the surface plasmon polariton, due to nonreciprocity of the structures. To study the dispersion properties associated with unidirectional propagation of magnetoplasmons in finite-size nanostructured waveguides, we have developed an efficient two dimensional numerical technique based on the magnetooptic aperiodic rigorous coupled wave analysis (MOaRCWA). We have shown that the one-way bandwidth can be controlled by an external magnetic field and by the permittivity and thickness of the dielectric guiding layer. To enable numerical simulation, we have utilized the configuration in which the magnetized section of a waveguide is along the direction of propagation sandwiched by the identical waveguide segments without magnetic field. We have also shown that the one-way bandwidth can be controlled by an external magnetic field and by the permittivity and thickness of the dielectric guiding layer.
Binary Classification of Mueller Matrix Images from an Optimization of Poincaré Coordinates
MEREDITH KUPINSKI, Jaden Bankhead, Adriana Stohn, and Russell Chipman
Doc ID: 287040 Received 20 Feb 2017; Accepted 18 Apr 2017; Posted 20 Apr 2017 View: PDF
Abstract: A new binary classification method for Mueller matrix images is presented which optimizes the Polar- ization State Analyzer (PSA) and the Polarization State Generator (PSG) using a statistical divergence between pixel values in two regions of an image. This optimization generalizes to multiple PSA/PSG pairs so that the classification performance as a function of number of polarimetric measurements can be considered. Optimizing PSA/PSG pairs gives insight into which polarimetric measurements are most useful for the binary classification. For example, in scenes with strong diattenuation, retardance, or depo- larization certain PSA/PSG pairs would make two regions in an image look very similar and other pairs would make the regions look very different. The method presented in is paper provides a quantitative method for ensuring the images acquired can be classified optimally.
The improvement of contrast sensitivity with practice is not compatible with a sensory threshold account
Joshua Solomon and Christopher Tyler
Doc ID: 277724 Received 28 Sep 2016; Accepted 17 Apr 2017; Posted 20 Apr 2017 View: PDF
Abstract: In forced-choice detection, incorrect responses are routinely ascribed to internal noise, because experienced psychophysical observers do not act as if they have a sensory threshold, below which all perceived intensities would be identical. To determine whether inexperienced observers have sensory thresholds, we examined psychometric functions (percent correct vs log contrast) for detection and detection in full-field, dynamic visual noise. Over 5 days, neither type of psychometric function changed shape, but both shifted leftwards, indicating increased sensitivity. These results are not consistent with a lowered sensory threshold, which would decrease psychometric slope. They are consistent with a combination of reduced internal additive noise and improved filtering of external noise.
Extended Taylor Frozen-Flow Hypothesis and Statistics of Optical Phase in Aero-Optics
Doc ID: 287471 Received 28 Feb 2017; Accepted 16 Apr 2017; Posted 25 Apr 2017 View: PDF
Abstract: We present an extended Taylor frozen-flow model for the statistics of the spatio-temporal disturbances of the index of refraction of air and the phase of an optical beam propagated through the turbulent boundary and shear layers in a high-Reynolds-number flow. By incorporating rapid random fluctuations of the flow velocity about a mean convection velocity and an anisotropic spatial power spectrum for the index of refraction, we show that the predictions of the model are consistent with the statistical data for the short-time-delay structure function of these disturbances based on observations by the Airborne Aero-Optical Laboratory. We also calculate the power spectrum of the temporal fluctuations of the optical phase, and discuss the predicted scaling behaviors of the spectrum in differentfrequency bands in the context of existing experimental observations.
Dual-wavelength polarimeter application in investigations of the optical activity of langasite crystal
Mykola Shopa, Nazar Ftomyn, and Yaroslav Shopa
Doc ID: 283805 Received 30 Dec 2016; Accepted 14 Apr 2017; Posted 25 Apr 2017 View: PDF
Abstract: A method of high accuracy polarimetry, which includes optical activity measurements systematic errors, was realized with dual-wavelength polarimeter for two wavelengths of 635 and 650 nm. Simultaneous measurements with neighboring wavelengths significantly improved the data processing, by increasing the amount of data to eliminate the systematic errors. For langasite crystal La₃Ga₅SiO₁₄ we measured temperature dependence of the gyration tensor component g₁₁. Our acquired value doesn’t exceed 0.47×10^-5 and is much smaller than previous results obtained by different experimental methods. Results presented in this paper correspond well with the calculated optical rotatory power from crystal structure data and polarizabilities of the atoms.
Influence of polarization aberrations on point images
Doc ID: 284535 Received 13 Jan 2017; Accepted 14 Apr 2017; Posted 25 Apr 2017 View: PDF
Abstract: In this article we derive Marechal type approximations forthe unpolarized imaging of points in presence of polarization aberrations.As the representation of the latter is ambiguous in general, we show the independence of the results on choices and suggest modified definitions.
Study of numerical stability of the C method and a perturbative technique to improve convergence
Lifeng Li and Xihong Xu
Doc ID: 286641 Received 14 Feb 2017; Accepted 13 Apr 2017; Posted 14 Apr 2017 View: PDF
Abstract: The translational coordinate transformation method (the C method) in grating theory is studied numerically and analytically. We first study the convergence characteristics of the C method by numerical computations in high floating-point data precisions. Guided by insights gained from this numerical study we analytically studied condition numbers of the most important eigenvalues of the eigenvalue problem of the C method. Asymptotic estimates of condition numbers of these eigenvalues and estimates of convergence rate of the error in satisfying Helmholtz equation by the eigenvectors are derived. These theoretical results explain well many observed numerical phenomena of the C method. Using the first-order perturbation theory of simple eigenvalues we analyze the effects of round-off errors on eigenvalue distribution and condition numbers. This leads to an extremely simple perturbative preconditioning technique that significantly improves the numerical stability of the C method with as little as just one line of code modification. The performance of the perturbative C method is not inferior to the C method preconditioned by the multi-linear parameterization technique. We recommend it as the preferred method for modeling deep and smooth gratings.
Enhancing spatio-chromatic representation with more-than-three color coding for image description
Ivet Rafegas, Javier Vazquez-Corral, Robert Benavente, Maria Vanrell, and Susana Alvarez
Doc ID: 285383 Received 24 Jan 2017; Accepted 10 Apr 2017; Posted 11 Apr 2017 View: PDF
Abstract: Extraction of spatio-chromatic features from color images is usually performed independently on each color channel. Usual 3D color spaces, such as RGB, present a high inter-channel correlation for natural images. This correlation can be reduced using color-opponent representations, but the spatial structure of regions with small color differences is not fully captured in two generic Red-Green and Blue-Yellow channels. To overcome these problems, we propose a new color coding that is adapted to the specific content of each image. Our proposal is based on two steps: (a) setting the number of channels to the number of distinctive colors we find in each image (avoiding the problem of channel correlation), and (b) building a channel representation that maximizes contrast differences within each color channel (avoiding the problem of low local contrast). We call this approach more-than-three color coding (MTT) to enhance the fact that the number of channels is adapted to the image content. The higher color complexity an image has, the more channels can be used to represent it. Here we select distinctive colors as the most predominant in the image, which we call color pivots, and we build the new color coding using these color pivots as a basis. To evaluate the proposed approach we measure its efficiency in an image categorization task. We show how a generic descriptor improves its performance at the description level when applied on the MTT coding.
Analyzing visual-search observers using eye trackingdata for digital breast tomosynthesis images
Zhengqiang Jiang, Mini Das, and Howard Gifford
Doc ID: 281347 Received 23 Nov 2016; Accepted 08 Apr 2017; Posted 14 Apr 2017 View: PDF
Abstract: Visual-search (VS) model observers have the potential to provide reliable predictions of human-observer performance in detection-localization tasks. The purpose of this work was to examine some characteristics of human gaze on breast images with the goal of informing the design of our VS observers. Using a helmet-mounted eye tracking system, we recorded the movement of gaze from human observers as they searched for masses in sets of 2D digital breast tomosynthesis (DBT) images. The masses in this study were of a single profile. The DBT images were extracted from image volumes reconstructed with the filtered backprojection method. Fixation times associated with observer points of interest (POIs) werecomputed from the observer data. We used k-mean clustering algorithm to get dwell times of gaze data. The dwell times were then compared to sets of morphological feature values extracted from the images. These features, extracted as cross-correlations involving the mass profile and the test image, included the matched filter (MF), gradient MF, Laplacian MF and adaptive MF. The adaptive MF combining four feature maps was computed using a hotelling discriminant generated from training data. For this investigation, we computed correlation coefficients between the fixation times and the feature values. We also conducted significance test by computing p-values of correlation coefficients for five features.
Adaptive Fusion of Human Visual Sensitive Featuresfor Surveillance Video Summarization
Md Musfequs Salehin and Manoranjan Paul
Doc ID: 283289 Received 20 Dec 2016; Accepted 08 Apr 2017; Posted 11 Apr 2017 View: PDF
Abstract: Surveillance video camera captures a large amount of continuous video stream every day. To analyze orinvestigate any significant events, it is laborious and boring job to identify these events from the hugevideo data if it is done manually. Existing approaches sometime neglect key frames with significant visualcontents and/or select some unimportant frames with low/no activity. To solve this problem, in thepaper a video summarization technique is proposed by combining three multi-modal human visual sensitivefeatures such as foreground objects, motion information and visual saliency. In a video stream,foreground objects are one of the most important content of a video as they contain more detail informationand play a major role for important events. Moreover, motion is another stimulus of a video whichattracts human visual attention significantly. To obtain this, motion information is calculated in spatialas well as frequency domain. Spatial motion information can select object motion accurately; however itis sensitive to illumination changes. On the other hand, frequency motion information is robust to illuminationchange, although it is easily affected by noise. Therefore, motion information both in spatialand frequency domain is employed. Furthermore, visual attention cue is a sensitive feature to measurethe indication of user’s attraction label for determining key frames. As these features individually cannotperform every well, they are combined to obtain better results. For this propose, an adaptive linearweighted fusion scheme is proposed to combine the features to rank video frames for summarization. Experimentalresults reveal that the proposed method outperforms the state of the art method
Critical Object Recognition in Millimeter-Wave Images with Robustness to Rotation and Scale
Hoda Mohammadzade, Benyamin Ghojogh, Sina Faezi, and Mahdi Shabany
Doc ID: 284432 Received 16 Jan 2017; Accepted 06 Apr 2017; Posted 11 Apr 2017 View: PDF
Abstract: Locating critical objects is crucial in various security applications and industries. For example, in security applications, such as in airports, these objects might be hidden or covered under shields or secret sheaths. Millimeter-wave images can be utilized to discover and recognize the critical objects out of the hidden cases without any health risk due to their non-ionizing feature. However, millimeter-wave images usually have waves in and around the detected objects, making object recognition difﬁcult. Thus, regular image processing and classiﬁcation methods cannot be used for these images and additional pre-processings and classiﬁcation methods should be introduced. This article proposes a novel pre-processing method for canceling rotation and scale using Principal Component Analysis (PCA). In addition, a two-layer classiﬁcation method is introduced and utilized for recognition. Moreover, a big dataset of millimeter-wave images is collected and created for experiments. Experimental results show that a typical classification method such as SVM can recognize 45.5% of a type of critical objects at 34.2% FAR, which is a drastically poor recognition. The same method within the proposed recognition framework achieves 92.9% recognition rate at 0.43% FAR which indicates a highly significant improvement. The signiﬁcant contribution of this work is to introduce a new method of analyzing millimeter-wave images based on machine vision and learning approaches, which is not yet widely noticed in the ﬁeld of millimeter-wave image analysis.
Principles of Image Reconstruction in OpticalInterferometry: Tutorial
Eric Thiebaut and John Young
Doc ID: 287964 Received 02 Mar 2017; Accepted 06 Apr 2017; Posted 19 Apr 2017 View: PDF
Abstract: This paper provides a general introduction to the problemof image reconstruction from interferometric data.A simple model of the interferometric observables isgiven and the issues arising from sparse Fourier dataare discussed. The effects of various regularizations aredescribed. In the proposed general framework, most existingalgorithms can be understood. For an astronomer,such an understanding is crucial not only for selectingand using an algorithm but also to ensure correct interpretationof the resulting image.
Human detection in occluded scenes through optically inspired multi-camera image fusion
Maryam Ghaneizad, Zahra Kavehvash, and Hamid Aghajan
Doc ID: 283113 Received 20 Dec 2016; Accepted 20 Mar 2017; Posted 24 Mar 2017 View: PDF
Abstract: In this paper, a novel approach for foreground extraction has been proposed based on a popular three-dimensional imaging technique in optics, named integral imaging. In this approach, multiple viewpoint images captured from a three-dimensional scene are used to extract range information of the scene, and effectively extract an object or a person, even in the presence of heavy occlusion. The algorithm consists of two parts: depth estimation and reconstruction of the targeted object at the estimated depth distance. Further processing on the resulting reconstructed image can lead to the detection of a face or a pedestrian in the scene, which may not otherwise be detectable due to partial occlusion in each of the views. The validity of our approach has been demonstrated by experimental results in different scenarios.