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Accepted papers to appear in an upcoming issue

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Improving Color Reproduction Accuracy of LCD-based Mobile Displays

Eric Kirchner, Ivo van der Lans, Francisco Martínez-Verdú, and Esther Perales

Doc ID: 274462 Received 26 Aug 2016; Accepted 27 Nov 2016; Posted 28 Nov 2016  View: PDF

Abstract: The default method for color representation on displays involves sRGB as device-independent encoding color space. For improving color reproduction accuracy, we develop a device-specific display characterization model for the Apple iPad Air 2. This is combined with an easy-to-implement new method to account for the influence of ambient illuminance. The combination is called the Mobile Display Characterization and Illumination (MDCIM) Model for the iPad Air 2, representing modern LCD displays. Seven observers performed psychophysical tests at ambient illuminance levels from 600 to 3000 lx. They visually compared colors of calculated images with those of physical RAL samples. The MDCIM model achieves similar color reproduction accuracy as when using the default method involving sRGB encoding at 1000 lx, while considerably improving color accuracy at other illuminance levels. At 600 lx 98% of the observations prefer images directly generated with the MDCIM model over those created using the default method. The average color reproduction accuracy improves by two categories on a five-point scale. At 3000 lx, the percentage of colors that is represented at least reasonably well increased from 0% to 60%.

Analysis of the average photon path length between two consecutive reflections from the cavity walls

Lazo Manojlovic

Doc ID: 270074 Received 08 Jul 2016; Accepted 24 Nov 2016; Posted 28 Nov 2016  View: PDF

Abstract: In this paper a general theoretical analysis of the average photon path length between two consecutive photon reflections from the cavity walls has been presented. The presented analysis relies only on the energy conservation law and the assumption of the uniform photon distribution within the cavity volume. The obtained general result coincides with the solution previously obtained but under more stringent conditions.

Selective excitation of higher order modes in etched gelatin coated few-mode fiber and demonstration of high relative humidity measurement

Partha Roy Chaudhuri and saba khan

Doc ID: 275671 Received 12 Sep 2016; Accepted 23 Nov 2016; Posted 28 Nov 2016  View: PDF

Abstract: We report here our experimental studies on efficient excitation of higher-order modes in a few-mode fiber realized through selective chemicaletchingof single-mode fiber, depositing a dynamic refractive-index profile coating (gelatin) and designing a well-performing high relativehumidity (73−99 %RH) sensor with sensitivity as high as ∼ 1.2 dBm/%RH and fast response (∼125 ms). The design relies on fixing quasiadiabatictransition of the single-mode−few-mode−single-mode configuration to launch light at angles corresponding to desired higher-ordermodes pushing more power into the coating. Our systematic study using the devised hybrid theoretical ray- and wave-optic model uniquelyinterprets the variety of experimental results.

Cytopathological Image Analysis using Deep Learning Networks in Microfluidic Microscopy for Label-free Leukaemia Cell-lines

G Gopakumar, K Hari Babu, Deepak Mishra, Sai Gorthi, and Sai Subrahmanyam Gorthi

Doc ID: 272778 Received 29 Jul 2016; Accepted 20 Nov 2016; Posted 21 Nov 2016  View: PDF

Abstract: Cytopathologic testing is one of the most critical steps in the diagnosis of diseases including cancer. However, the task is laborious and skill demanding. Associated high cost and low throughput drew considerable interest in automating the testing process. Several neural network architectures were designed to provide human expertise to machines. In this paper, we explore and propose the feasibility of using deep learning networks for cytopathologic analysis by performing the classification of three important unlabeled, unstained leukemia cell-lines (K562, MOLT and HL60). The cell images used in the classification are captured using a low-cost, high-throughput cell imaging technique: the microfluidics based imaging flow cytometry. We demonstrate that without any conventional fine segmentation followed by explicit feature extraction, the proposed deep learning algorithms effectively classify the coarsely localised cell lines. We show that the designed deep belief network as well as the deeply pre-trained convolutional neural network outperforms the conventionally used decision systems and are important in medical domain where the availability of labelled data is limited for training. We hope that our work enables the development of a clinically significant high-throughput microfluidic microscopy based tool for disease screening/triaging especially in resource limited settings.

Simple, flexible and accurate phase retrieval method for generalized phase-shifting interferometry

Kohei Yatabe, Kenji Ishikawa, and Yasuhiro Oikawa

Doc ID: 278085 Received 03 Oct 2016; Accepted 19 Nov 2016; Posted 22 Nov 2016  View: PDF

Abstract: This paper presents a non-iterative phase retrieval method from randomly phase-shifted fringe images. By combining the hyperaccurate least squares ellipse fitting method with the subspace method (which is usually called the principle component analysis), a fast and accurate phase retrieval algorithm is realized. The proposed method can be said as: (1) simple because it can be easily coded without iteration, initial guess nor tuning parameter; (2) flexible because totally random phase-shifting steps and any number of fringe images greater than two are acceptable without any specific treatment; (3) accurate because the hyperaccurate least squares method and the modified subspace method enable phase retrieval with small error as shown by the simulations. A MATLAB code, which is used in the experimental section, is provided within the paper to demonstrate its simplicity and easiness.

Vector and matrix states for Mueller matrices of nondepolarizing optical media

Oriol Arteaga, Ertan Kuntman, and mehmet kuntman

Doc ID: 278099 Received 03 Oct 2016; Accepted 18 Nov 2016; Posted 21 Nov 2016  View: PDF

Abstract: Nondepolarizing Mueller matrices contain up to seven independent parameters. However these seven parameters typically do not appear explicitly among the measured 16 parameters of a Mueller matrix so that they are not directly accessible for a physical interpretation. This work shows that all the information contained in a nondepolarizing Mueller matrix can be conveniently expressed in terms of a four component covariance vector state or a generating 4x4 matrix that can be understood as a matrix state. The generating matrix, besides being directly related to the nondepolarizing Mueller matrix, mimics all properties of the Jones matrix and provides a powerful mathematical tool for formulating all properties of nondepolarizing systems, including the Mueller symmetries and the anisotropy coefficients.

Asymptotic model for finite-element calculations ofdiffraction by shallow metallic surface-relief gratings

Cinthya Rivas, Manuel Solano, Rodolfo Rodriguez, Peter Monk, and Akhlesh Lakhtakia

Doc ID: 270743 Received 18 Jul 2016; Accepted 16 Nov 2016; Posted 16 Nov 2016  View: PDF

Abstract: We have formulated an asymptotic model for implementation in the finite-element method to calculatediffraction from a planar multilayered structure having a shallow surface-relief grating. The thin gratinglayer containing the shallow grating is replaced by a planar interface with transmission conditions thatdiffer from the standard continuity conditions, thereby eliminating the necessity of representing the gratinglayer by a fine mesh. The parameters defining the shallow surface-relief grating are thereby removedfrom the geometry to the transmission conditions. Adoption of the asymptotic model will considerablyreduce the computational cost of optimizing the grating shape, since there is no need to re-mesh at everyoptimization step.

An Approach to Atmospheric Laser-PropagationTheory Based on the Extended Huygens-FresnelPrinciple and a Self-Consistency Concept

Erik Bochove and Venkata Gudimetla

Doc ID: 270930 Received 19 Jul 2016; Accepted 16 Nov 2016; Posted 17 Nov 2016  View: PDF

Abstract: We propose a self-consistency condition based on the extended Huygens-Fresnel (eHF) principle, which we apply to thepropagation kernel of the mutual coherence function (MCF) of a partially coherent laser beam propagating through a turbulentatmosphere. With the assumption of statistical independence of turbulence in neighboring propagation segments an integralequation in the kernel results, which possesses a Gaussian solution with dependence on transverse coordinates that is identicalto a previous Gaussian formulation by H. T. Yura (Appl. Opt. 11, 1399 (1972)), but differs in the transverse coherence length’sdependence on propagation distance, so that this established version is in violation of our self-consistency principle. Ourformulation has one free parameter, which in the context of the Kolmogorov theory is independent of turbulence strength andpropagation distance and its value we determined by numerically fitting to the rigorous beam propagation theory of Yura andHanson (J. Opt. Soc. Am. A, 6, 564(1989)), demonstrating in addition a significant improvement over other Gaussian models.

Generalized vector wave theory for ultra-high resolution confocal optical microscopy

Xiangsheng Xie, Ken Yang, and Jianying Zhou

Doc ID: 274332 Received 23 Aug 2016; Accepted 16 Nov 2016; Posted 18 Nov 2016  View: PDF

Abstract: Polarization modulation of a tightly focused beam in a confocal imaging scheme is considered for both incident and collected light fields. Rigorous vector wave theory of a confocal optical microscopy is developed, which provides clear physical pictures without the requirement for fragmentary calculations. Multiple spatial modulations on polarization, phase or amplitude of the illuminating and the detected beams can be mathematically described by a uniform expression. Linear and nonlinear excitation schemes are derived with tailored excitation and detection fields within this generalized theory, whose results show that the ultimate resolution achieved with the linear excitation can reach one fifth of excitation wavelength (or λ/5), while the nonlinear excitation scheme gives rise to a resolution better than λ/12 for two-photon fluorescence excitation and λ/20 for three-photon fluorescence excitation. Hence the resolution of optical microscopy with a near infrared excitation can routinely reach sub-60 nm. In addition, simulations for confocal laser scanning microscopy are carried out with both linear excitation scheme and fluorescent one respectively.

Characterisation, design, and optimisation of a two-pass twisted nematic liquid crystal spatial light modulator system for arbitrary complex modulation

Alexander Macfaden and Tim Wilkinson

Doc ID: 272573 Received 18 Aug 2016; Accepted 15 Nov 2016; Posted 16 Nov 2016  View: PDF

Abstract: Arbitrary 2D complex modulation of an optical field is a powerful tool for coherent optical systems. No single spatial light modulator (SLM) offers true arbitrary complex modulation, but they can be combined in order to achieve this. In this work, two sides of a twisted nematic (TN) liquid crystal SLM are used sequentially to implement different arbitrary modulation schemes. In order to fully explore and exploit the rich modulation behaviour offered by a TN device a generalised Jones matrix approach is used. A method for in situ characterisation of the SLM inside the two-pass system is demonstrated, where each side of the SLM is independently characterised. This characterisation data is then used to design appropriate polariser configurations to implement arbitrary complex modulation schemes. Finally, an in situ optimisation technique which corrects states by applying a translation in the complex plane is demonstrated. This technique can correct both for variations across the SLM and bulk changes in the SLM behaviour due to changing temperature.

Amplitude and phase beam shaping for highest sensitivity in side-wall angle detection

Luca Cisotto and H. Urbach

Doc ID: 269100 Received 27 Jun 2016; Accepted 15 Nov 2016; Posted 16 Nov 2016  View: PDF

Abstract: In integrated circuits (IC) manufacturing, specific structures are used as tools to evaluate the quality of the lithographic process, these structures are often gratings of which the shape is described by few parameters of which in particular the side-wall angle suffers from considerable inaccuracies. Using scalar diffraction theory, we investigate whether a properly shaped cylindrical focused probing beam could increase the ability to detect tiny changes of this angle in the case of a cliff-like structure, modeled as a phase object. This paper describes the theoretical formulation used to calculate the optimized beam and compares its performance with the case of a cylindrically focused plane wave.

Adaptive single-pixel imaging based on guided coefficients

Yaoran Huo, Hongjie He, Fan Chen, and Hengming Tai

Doc ID: 273532 Received 11 Aug 2016; Accepted 13 Nov 2016; Posted 16 Nov 2016  View: PDF

Abstract: The existing adaptive single-pixel imaging methods suffer from a waste of sampling resource. The sampling resource is not used adequately for superior localization of significant coefficients and reconstruction. In this paper, an adaptive single-pixel imaging method via the guided coefficients in the Haar wavelet tree is proposed. The goal is to achieve high quality imaging with less sampling resource. The guided coefficients are selected from the un-sampled coefficients by a proposed same-scale prediction method based on the sampled coefficients. These guided coefficients are used to localize the significant coefficients with higher resolution belonging to the sampled coefficients and the significant coefficients belonging to the guided coefficients by a proposed guided prediction method. The significant guided coefficients are then used in the composite reconstruction method to reconstruct the image. Performance analysis shows that the proposed method reduces waste of sampling resource and localizes more significant coefficients. Simulation results demonstrate that the proposed method improves the imaging quality in terms of peak noise-to-ratio up to 29.7 dB for the images containing regular and chaotic textures in the noise-free environment. The sampling rate for the same imaging quality can be reduced up to 56%. Under the noisy condition, the proposed method also achieves better imaging quality at lower sampling rate.

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