Accepted papers to appear in an upcoming issue
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The polarization-dependent effects of Airy beam due to the spin-orbit coupling
Hehe Li, Jingge Wang, Miaomiao Tang, and Xinzhong Li
Doc ID: 293164 Received 21 Apr 2017; Accepted 22 May 2017; Posted 22 May 2017 View: PDF
Abstract: We investigate the polarization-dependent effects when a circularly polarized Airy beam propagates in an inhomogeneous medium. It shows that there are some interesting polarization-dependent phenomena induced by the spin-orbit coupling: the circularly polarized Airy beam will follow a polarization-dependent trajectory in an inhomogeneous medium, and there are the polarization-dependent self-acceleration of the Airy beam in the linear-index inhomogeneous medium and the polarization-dependent rotation of the Airy beam in the quadratic-index inhomogeneous medium. These polarization-dependent phenomena are different from the manifestation of the "traditional" spin Hall effect of light beam which just displays the polarization-dependent transverse deflection of the beam.
Three-Dimensional Electromagnetic Imaging ofDielectric Targets by means of the MultiscalingInexact-Newton Method
Marco Salucci, Giacomo Oliveri, nicola anselmi, federico viani, alessandro fedeli, Matteo Pastorino, and Andrea Randazzo
Doc ID: 282666 Received 16 Dec 2016; Accepted 18 May 2017; Posted 19 May 2017 View: PDF
Abstract: A novel approach for three-dimensional electromagnetic imaging is presented. This technique is a combinationof an iterative multiscaling approach with an inexact-Newton method. The multiscaling procedureallows one to iteratively focus the region of interest on the detected target, whereas the inexact-Newtonmethod provides an efficient regularized solution of the nonlinear electromagnetic inverse scatteringproblem for each scaling step. The proposed method is validated against numerical data with differentconfiguration settings. A preliminary experimental validation is also reported.
Fast computer hologram generation by flexible-ratio adaptive point-spread spherical wave synthesis
Yutaka Mori and Yuto Arai
Doc ID: 287128 Received 23 Feb 2017; Accepted 15 May 2017; Posted 16 May 2017 View: PDF
Abstract: We propose a flexible-ratio adaptive point-spread spherical wave synthesis method for fast computergeneratedhologram (CGH) calculation. The conventional adaptive point-spread algorithm uses a fixedratio between the major and minor axes of the point source, whereas the proposed method uses flexibleratiosources, i.e., ellipses, for more effective calculation. Numerical simulation was conducted to validatethe proposed method. The results show that the proposed method has the potential to achieve fastercalculation compared to the calculation in conventional methods without significant image degradation.
Stochastic Calculus Analysis of Optical Time-of-Flight Range Imaging and Estimation of Radial Motion
Doc ID: 280668 Received 11 Nov 2016; Accepted 12 May 2017; Posted 12 May 2017 View: PDF
Abstract: Time-of-flight range imaging is analysed using stochastic calculus. Through a series of interpretations and simplifications, the stochastic model leads to two methods for estimating linear radial velocity: maxi- mum likelihood estimation on the transition probability distribution between measurements; and a new method based on analysing the measured correlation waveform and its first derivative. The methods are tested in a simulated motion experiment from (−40)—(+40) m/s, with data from a camera imaging an object on a translation stage. In tests maximum likelihood is slow and unreliable, but when it works it estimates the linear velocity with standard deviation of 1 m/s or better. In comparison the new method is fast and reliable but works in a reduced velocity range of (−20)—(−20) m/s with standard deviation ranging from 3.5 m/s to 10 m/s.
Wide Bandwidth, Millimeter-resolution InverseSynthetic Aperture Radar Imaging
Henry Everitt, Jonathan Richard, Martin Heimbeck, and L Autin
Doc ID: 282562 Received 09 Dec 2016; Accepted 12 May 2017; Posted 15 May 2017 View: PDF
Abstract: The combination of wide bandwidth W-band inverse synthetic aperture radar imagery and high fidelity numericalsimulations has been used to identify distinguishing signatures from simple metallic and dielectric targets. Targetsare located with millimeter-scale accuracy using super-resolution techniques, and Radon transformreconstructions of the returns from rotated targets approached the image quality of the complete data set in afraction of the time by sampling as few as ten angles. The limitations of shooting-and-bouncing ray simulations athigh frequencies are illustrated through a critical comparison of their predictions with the measured data andmethod of moments simulations, indicating the importance of accurately capturing the obfuscating role played bymultipath interference in complex targets.
Interaction description of light propagation
Doc ID: 284916 Received 16 Jan 2017; Accepted 08 May 2017; Posted 08 May 2017 View: PDF
Abstract: The interaction between real and virtual point emitters is presented as propagation principle of light under arbitrary spatial coherence. It is supported on a geometrical interpretation of the two-point correlation and the introduction of the geometrical potential. This principle and the spectrum of classes of point emitters constitute a complete theoretical model that offers a unified phenomenological framework for interference and diffraction not only of light but also of single particles, which is not possible in the conventional formalism based on the wave superposition principle.
Optimal configuration of static Mueller imagers for target detection
Francois Goudail, Matthieu Boffety, and stephane roussel
Doc ID: 287748 Received 01 Mar 2017; Accepted 07 May 2017; Posted 08 May 2017 View: PDF
Abstract: We investigate the target detection performance of static Mueller imagers that implement a fixed number of illumination and analysis polarization states. Using a maximin approach, we demonstrate that the optimal sets of measurement vectors consist in regular tetrahedra on the Poincar\'e sphere and that in this case, the obtained target/background contrast has a very simple expression. We then derive a universal lower bound on the contrast ratio between the best channel of a static imager and a fully adaptive one, and in a special case of practical interest, we demonstrate that this ratio is bounded and always larger than $1/9$. This is very important in practice since static imagers are much easier to build and operate. Our results show that they constitute a good alternative where ultimate contrast improvement is not necessary.
Freeform Aberrations in Phase Space: An Example
Doc ID: 286687 Received 14 Feb 2017; Accepted 05 May 2017; Posted 05 May 2017 View: PDF
Abstract: We consider how optical propagation and aberrations of freeform systems can be formulated in phase space. As an example system, a freeform prism is analysed and discussed. Symmetry considerations, and their group theory descriptions are given some importance. Numerical aberrations are also highlighted and put into context of the underling aberration theory.
Illuminant estimation in multispectral imaging
Haris Ahmad Khan, Jean-Baptiste THOMAS, Jon Hardeberg, and Olivier Laligant
Doc ID: 282049 Received 05 Dec 2016; Accepted 05 May 2017; Posted 08 May 2017 View: PDF
Abstract: With the advancement in sensor technology, use of multispectral imaging is gaining wide popularity forcomputer vision applications. Multispectral imaging is used to achieve better discrimination between theradiance spectra, as compared to the color images. However, it is still sensitive to illumination changes.This study evaluates the potential evolution of illuminant estimation models from color to multispectralimaging. We first present a state of the art on computational color constancy and then extend a set ofalgorithms to use them in multispectral imaging. We investigate the influence of camera spectral sensitivitiesand number of channels. Experiments are performed on simulations over hyperspectral data. Theoutcomes indicate that extension of computational color constancy algorithms from color to spectral, givepromising results and may have the potential to lead towards efficient and stable representation acrossilluminants. However, it is highly dependant on spectral sensitivities and noise. We believe that the developmentof illuminant invariant multispectral imaging systems will be a key enabler for further use ofthis technology.
Fast and accurate 3D PSF computation for fluorescence microscopy
Jizhou LI, Feng Xue, and Thierry Blu
Doc ID: 285885 Received 31 Jan 2017; Accepted 04 May 2017; Posted 05 May 2017 View: PDF
Abstract: The point-spread function (PSF) plays a fundamental role in fluorescence microscopy. A realistic and accurately calculated PSF model can significantly improve the performance in 3D deconvolution microscopy and also the localization accuracy in single-molecule microscopy. In this work, we propose a fast and accurate approximation of the Gibson-Lanni model, which has been shown to represent the PSF suitably under a variety of imaging conditions. We express the Kirchhoff's integral in this model as a linear combination of rescaled Bessel functions, thus providing an integral-free way for the calculation. The explicit approximation error in terms of parameters is given numerically. Experiments demonstrate that the proposed approach results in a significantly smaller computational time compared with current state-of-the-art techniques to achieve the same accuracy. This approach can also be extended to other microscopy PSF models.
Color Opponency: A Tutorial
Steven Shevell and Paul Martin
Doc ID: 285192 Received 19 Jan 2017; Accepted 03 May 2017; Posted 08 May 2017 View: PDF
Abstract: In dialog, two color scientists introduce the topic of color opponency, as seen from theviewpoints of color appearance (psychophysics) and measurement of nerve cell responses(physiology). Points of difference, as well as points of convergence between theseviewpoints are explained. Key experiments from the psychophysical and physiologicalliterature are covered in detail to help readers from these two broad fields understandeach other's work.
Temporal coherence of a low-power erbium-doped fiber laser with spectrally broadened output
R. Vijaya and Suchita Yadav
Doc ID: 287030 Received 20 Feb 2017; Accepted 01 May 2017; Posted 03 May 2017 View: PDF
Abstract: The temporal coherence of spectrally selected output from a CW broadband erbium doped fiber ring laser (EDFRL) based on four wave mixing is characterized using a fiber-optic Mach-Zehnder interferometer. The visibility is found to be comparable to that of a standard narrow-linewidth tunable laser when their spectral widths are matched using an intra-cavity filter in EDFRL. But its visibility is distinctly higher than two other broadband sources (super-luminescent diode and amplified spontaneous source) even when their spectral widths are matched, establishing that the cavity effect aids the coherence in EDFRL by mitigating the phase noise from four wave mixing.
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.