This PDF file contains the front matter associated with SPIE Proceedings Volume 9970, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

A compact light detection and ranging (LiDAR) system provides aerosols profile measurements by identifying the aerosol scattering ratio as function of the altitude. The aerosol scattering ratios are used to obtain multiple aerosol intensive ratio parameters known as backscatter color ratio, depolarization ratio and lidar ratio. The aerosol ratio parameters are known to vary with aerosol type, size, and shape. Different methods in the literature are employed for detection and classification of aerosol from the measurements. In this paper, a comprehensive review for aerosol detection methods is presented. In addition, results of implemented methods of quantifying aerosols in the atmosphere on real data are compared and presented showing how the backscatter color, depolarization and lidar ratios vary with presence of aerosols in the atmosphere.

We develop a multi-band spectrometer with a few spatially parallel optical arms for the combined processing of their data flow. Such multi-band capability has various applications in astrophysical scenarios at different scales: from objects in the distant universe to planetary atmospheres in the Solar system. Each optical arm exhibits original performances to provide parallel multi-band observations with different scales simultaneously. Similar possibility is based on designing each optical arm individually via exploiting different materials for acousto-optical cells operating within various regimes, frequency ranges and light wavelengths from independent light sources. Individual beam shapers provide both the needed incident light polarization and the required apodization to increase the dynamic range of a system. After parallel acousto-optical processing, data flows are united by the joint CCD matrix on the stage of the combined electronic data processing. At the moment, the prototype combines still three bands, i.e. includes three spatial optical arms. The first low-frequency arm operates at the central frequencies ~60-80 MHz with frequency bandwidth ~40 MHz. The second arm is oriented to middle-frequencies ~350-500 MHz with frequency bandwidth ~200-300 MHz. The third arm is intended for ultra-high-frequency radio-wave signals about 1.0-1.5 GHz with frequency bandwidth <300 MHz. To-day, this spectrometer has the following preliminary performances. The first arm exhibits frequency resolution ~20 KHz; while the second and third arms give the resolution ~150-200 KHz. The numbers of resolvable spots are 1500- 2000 depending on the regime of operation. The fourth optical arm at the frequency range ~3.5 GHz is currently under construction.

Depth cues and full-parallax are crucial issues in the calculation of computer-generated holograms (CGHs) for perfect holographic three-dimensional (3-D) display. In order to accelerate the speed of generating CGHs and improve the display quality, three layer-oriented methods are investigated in this paper. The first method is based on angularspectrum, which can provide accurate depth cues. The second method is based on inverse Fresnel diffraction layered holographic stereogram to provide accurate depth information as well as correct occlusion effect. The third method is proposed to generate zoomable 3-D CGHs using layer-based shifted Fresnel diffraction. Numerical simulations and optical experiments have demonstrated that the proposed methods can reconstruct quality 3-D images.

We introduce a polyvinil alcohol/acrylamide (PVA/AA) photopolymer compound in a holographic memory testing platform to provide experimental results for storage and retrieval of information. We also investigate different codification schemes for the data pages addressed onto the parallel-addressed liquid crystal on silicon (PA-LCoS) device, used as the data pager, such as binary intensity modulation (BIM), and hybrid-ternary modulation (HTM), and we will see that an actual approximation for HTM can be obtained with a PA-LCoS device. We will also evaluate the effect of the time fluctuations in the PA-LCoS microdisplays onto the BIM and HTM regimes. Good results in terms of signal-tonoise ratio and bit-error ratio are provided with the experimental system and using the PVA/AA photopolymer produced in our lab, thus showing its potential and interest for future research focused on this material with highly tunable properties.

We study the effect of graphene oxide (GrO) on the switching voltage of polymer dispersed liquid crystal (PDLC). The threshold voltage decreases with addition of GrO nanoparticles. Scanning electron microscopy (SEM) supported that the size of LC droplets in GrO-doped PDLC increase in comparison with non-doped one. PDLC:GrO layer was combined with Bi₁₂SiO₂₀ (BSO) inorganic substrate into a hybrid structure and based on the surface activated photorefractive phenomena typical for BSO, it allows the opaque-transparent states to be all optically controlled, operating faster and requiring less intensity due to the GrO addition in PDLC.

Applying of a phase-shifting digital holography combined with compressive sensing to inspect the soldering quality of surface mount technology (SMT) which is a method for producing electronic circuits. In SMT, the components are mounted and connected with each other directly onto the surface of printed circuit boards (PCBs). By reconstructing the multidimensional images from a few samples of SMT, the results are solved by an optimization problem. In this paper, two problems have been concerned. The first one is to examine the devices and the soldering quality of connections between them, which are in micro-scaled. The second is to observe the effect of heat treatment of soldering material and devices on the surface mount board.

Digital Micro-mirror Device (DMD) is an important tool in holographic display owning high-speed refresh rate and good diffraction efficiency. However, the reconstruction light source has great impact to image quality. A new holographic display system based on DMD for using light-emitting diodes (LEDs), is proposed in this paper. LEDs are chosen as light source to replace the laser, since it can reduce the speckle noise effectively, which is caused by both temporal and spatial coherence of laser. In order to solve the problem using LED as DMD holographic display light source, the characteristics of DMD as the display device for holographic displays are studied. An aspheric collimator for LED is used to improve the optical efficiency. A spatial filter is used to improve the coherence. The experimental results show that this lighting system has a good display quality.

Virtual reality (VR)/ augmented reality (AR) applications allow users to view artificial content of a surrounding space simulating presence effect with a help of special applications or devices. Synthetic contents production is well known process form computer graphics domain and pipeline has been already fixed in the industry. However emerging multimedia formats for immersive entertainment applications such as free-viewpoint television (FTV) or spherical panoramic video require different approaches in content management and quality assessment. The international standardization on FTV has been promoted by MPEG. This paper is dedicated to discussion of immersive media distribution format and quality estimation process. Accuracy and reliability of the proposed objective quality estimation method had been verified with spherical panoramic images demonstrating good correlation results with subjective quality estimation held by a group of experts.

A simple method to evaluate the focal length of concave mirrors is proposed. The inverse ray-tracing approach of the Ronchi test is used in the measurement stage. The theoretical principles are given and a numerical method for ronchigram processing is proposed. The results verify the feasibility of the proposal.

Biometrics refers to identify people through their physical characteristics or behavior such as fingerprints, face, DNA, hand geometries, retina and iris patterns. Typically, the iris pattern is to acquire in short distance to recognize a person, however, in the past few years is a challenge identify a person by its iris pattern at certain distance in non-cooperative environments. This challenge comprises: 1) high quality iris image, 2) light variation, 3) blur reduction, 4) specular reflections reduction, 5) the distance from the acquisition system to the user, and 6) standardize the iris size and the density pixel of iris texture. The solution of the challenge will add robustness and enhance the iris recognition rates. For this reason, we describe the technical issues that must be considered during iris acquisition. Some of these considerations are the camera sensor, lens, the math analysis of depth of field (DOF) and field of view (FOV) for iris recognition. Finally, based on this issues we present experiment that show the result of captures obtained with our camera at distance and captures obtained with cameras in very short distance.

The holoprinter technology based on holographic stereograms has generated a fast development in holographic display applications by the holographic recording of a 2D image sequence with information of a 3D scene, which could be real or computer generated. The images used in holographic stereograms initially start from the acquisition of the different image perspectives of the 3D scene by the re-centering camera configuration and then, this images must be rearranged before the optical recording. This paper proposes a method to acquire the required images or hogel images in one step without using rearrange algorithms, the method uses a virtual camera that moves along a virtual rail by conventional computer graphics software. The proposed method reduced the time required to obtain the hogel images and enhance the quality of the 3D holographic images; it also can be applied in different computer graphics software. To validate the method, a full parallax holographic stereogram was made for a computer generated object.

A hybrid annealed proton exchange (APE) waveguide with a vertically integrated arsenic trisulfide (As₂S₃) waveguide on a lithium niobate (LiNbO₃) substrate is used to create an optical phased array (OPA) that allows for the non-mechanical steering of 1550 nm light on an integrated optic platform. The high electro-optic coefficient of the x-cut y-propagating LiNbO₃ (r33 = 30.8 pm/V) is utilized by electrode structures fabricated on the LiNbO₃ substrate to create a low-power, lowloss beam steering with high-speed bandwidths, capable of 10 GHz and larger as demonstrated by commercial LiNbO₃ modulators. The As₂S₃ waveguide is introduced because of its high refractive index, which leads to a highly confined optical mode. Design and fabrication are presented for a large full width steering angle of 34°, representing an order of magnitude improvement over low-confinement, diffused LiNbO₃ waveguides and two orders of magnitude improvement over other reported LiNbO₃ OPAs.

Nonuniformity in FPAs (focal plane arrays) is a common, although undesirable, characteristic arising from small differences in the responsivity of individual detectors. Now there are many scene-based nonuniformity correction algorithms. In these correction algorithms, interframe registration based nonuniformity correction algorithm is a principal type. The core of interframe registration based nonuniformity correction algorithm is accurate image registration. However, because of the existence of the nonuniformity, the values of the adjacent columns or rows of the image with noise are so close that it is difficult to distinguish them. We find it is difficult to achieve the corresponding rows or columns registration between two frames accurately. It will lead to the wrong registration that will affect the nonuniformity correction effect. In this method, we propose a nonuniformity correction algorithm based on subspace projection registration. By projecting the rows and columns of the image on to their corresponding subspace respectively, we can realize the dimension reduction of the row space and the column space. As a result, the value differences between the adjacent rows or the adjacent columns of the image can be amplified. Then the algorithm can identify the corresponding rows and columns between two frames, enabling accurate image registration. Experiments demonstrate that our algorithm achieve accurate image registration and outstanding correction effect.

3D-scene acquisition and representation is important in many areas ranging from medical imaging to visual entertainment application. In this regard, optical imaging acquisition combined with post-capture processing algorithms enable the synthesis of images with novel viewpoints of a scene. This work presents a new method to reconstruct a pair of stereoscopic images of a 3D-scene from a multi-focus image stack. A conventional monocular camera combined with an electrically tunable lens (ETL) is used for image acquisition. The captured visual information is reorganized considering a piecewise-planar image formation model with a depth-variant point spread function (PSF) along with the known focusing distances at which the images of the stack were acquired. The consideration of a depth-variant PSF allows the application of the method to strongly defocused multi-focus image stacks. Finally, post-capture perspective shifts, presenting each eye the corresponding viewpoint according to the disparity, are generated by simulating the displacement of a synthetic pinhole camera. The procedure is performed without estimation of the depth-map or segmentation of the in-focus regions. Experimental results for both real and synthetic data images are provided and presented as anaglyphs, but it could easily be implemented in 3D displays based in parallax barrier or polarized light.

In image restoration problems it is commonly assumed that image degradations are linear. In real-life this assumption is not always satisfied causing linear restoration methods fail. In this work, we present the design of an image restoration filtering based on genetic programming. The proposed filtering is given by a secuence of basic mathematical operators that allows to retrieve an undegraded image from an image degraded with noise. Computer simulations results obtained with the proposed algorithm in terms of objective metrics are analyzed and discussed by processing images degraded with noise. The obtained results are compared with those obtained with existing linear filters.

The Advance Radiographic Capability (ARC) at the National Ignition Facility (NIF) is a laser system that employs up to four petawatt (PW) lasers to produce a sequence of short-pulse kilo-Joule laser pulses with controllable delays that generate X-rays to provide backlighting for high-density internal confinement fusion (ICF) capsule targets. Multi-frame, hard-X-ray radiography of imploding NIF capsules is a capability which is critical to the success of NIF's missions. ARC is designed to employ up to eight backlighters with tens-of-picosecond temporal resolution, to record the dynamics and produce an X-ray "motion picture" of the compression and ignition of cryogenic deuterium-tritium targets. ARC will generate tens-of-picosecond temporal resolution during the critical phases of ICF shots. Additionally, ARC supports a variety of other high energy density experiments including fast ignition studies on NIF. The automated alignment image analysis algorithms use digital camera sensor images to direct ARC beams onto the tens-of-microns scale metal wires. This paper describes the ARC automatic alignment sequence throughout the laser chain from pulse initiation to target with an emphasis on the image processing algorithms that generate the crucial alignment positions for ARC. The image processing descriptions and flow diagrams detail the alignment control loops throughout the ARC laser chain beginning in the ARC high-contrast front end (HCAFE), on into the ARC main laser area, and ending in the ARC target area.

Pattern recognition and localization along with feature extraction are image processing applications of great interest in defect inspection and robot vision among others. In comparison to purely digital methods, the attractiveness of optical processors for pattern recognition lies in their highly parallel operation and real-time processing capability. This work presents an optical implementation of the generalized Hough transform (GHT), a well-established technique for the recognition of geometrical features in binary images. Detection of a geometric feature under the GHT is accomplished by mapping the original image to an accumulator space; the large computational requirements for this mapping make the optical implementation an attractive alternative to digital- only methods. Starting from the integral representation of the GHT, it is possible to device an optical setup where the transformation is obtained, and the size and orientation parameters can be controlled, allowing for dynamic scale and orientation-variant pattern recognition. A compact system for the above purposes results from the use of an electrically tunable lens for scale control and a rotating pupil mask for orientation variation, implemented on a high-contrast spatial light modulator (SLM). Real-time (as limited by the frame rate of the device used to capture the GHT) can also be achieved, allowing for the processing of video sequences. Besides, by thresholding of the GHT (with the aid of another SLM) and inverse transforming (which is optically achieved in the incoherent system under appropriate focusing setting), the previously detected features of interest can be extracted.

The perspective and lens distortions induced by the imaging system of a camera device are corrected by using an elementary geometrical approach. We propose a simple method based on the use of a crossed grating in the reference plane and a phase demodulation process. Preliminary results showing the performance of the proposed method are discussed.

In this paper, a classification method for classifying subjects’ ability to follow some predefined trajectories is proposed using phase only filter (POF) [1]. In this research, we use three predefined trajectory patterns of different difficulty levels, and a set of data comprising four different classes of movements. We propose a POF to classify the data in those classes. POF can be assumed as a Complex Match Filter (CMF) where the amplitude of the object function is set to unity. The POF searches the entire image to find a match to the input filter. The trajectory in all three patterns contains edges and sharp turns which could considerably help to distinguish between the classes. Therefore, in this method, the reference pattern is segmented to several parts and critical segments of the trajectory used as an input filter or the pattern to search for. The classification task is applied for each pattern separately and the results obtained are fused based on different weights. The optimum weights for the fusion are obtained by using the training data and the linear regression technique.

Every summer in the National Ignition Facility (NIF) at Lawrence Livermore National Laboratory, students are brought in to gain interesting research and development experience. In this work, we will review some case studies of past research experiences with students inside and outside NIF, that led to successful journal and conference publications. Several of these works will be reviewed to demonstrate how problems were chosen and defined so that meaningful results could be obtained within a limited time frame. It is anticipated that success with such projects will go a long way in motivating students in their future graduate career. Projects from laser measurement, optical computing and application of matched filtering in laser beam alignment will be reviewed to demonstrate this approach.

The problem of 3D pose recognition of a rigid object is difficult to solve because the pose in a 3D space can vary with multiple degrees of freedom. In this work, we propose an accurate method for 3D pose estimation based on template matched filtering. The proposed method utilizes a bank of space-variant filters which take into account different pose states of the target and local statistical properties of the input scene. The state parameters of location coordinates, orientation angles, and scaling parameters of the target are estimated with high accuracy in the input scene. Experimental tests are performed for real and synthetic scenes. The proposed system yields good performance for 3D pose recognition in terms of detection efficiency, location and orientation errors.

The linear canonical transform (LCT) is essential in modeling a coherent light field propagation through first-order optical systems. Recently, a generic optical system, known as a Quadratic Phase Encoding System (QPES), for encrypting a two-dimensional (2D) image has been reported. It has been reported together with two phase keys the individual LCT parameters serve as keys of the cryptosystem. However, it is important that such the encryption systems also satisfies some dynamic security properties. Therefore, in this work, we examine some cryptographic evaluation methods, such as Avalanche Criterion and Bit Independence, which indicates the degree of security of the cryptographic algorithms on QPES. We compare our simulation results with the conventional Fourier and the Fresnel transform based DRPE systems. The results show that the LCT based DRPE has an excellent avalanche and bit independence characteristics than that of using the conventional Fourier and Fresnel based encryption systems.

Current search engines are based upon search methods that involve the combination of words (text-based search); which has been efficient until now. However, the Internet’s growing demand indicates that there’s more diversity on it with each passing day. Text-based searches are becoming limited, as most of the information on the Internet can be found in different types of content denominated multimedia content (images, audio files, video files). Indeed, what needs to be improved in current search engines is: search content, and precision; as well as an accurate display of expected search results by the user. Any search can be more precise if it uses more text parameters, but it doesn’t help improve the content or speed of the search itself. One solution is to improve them through the characterization of the content for the search in multimedia files. In this article, an analysis of the new generation multimedia search engines is presented, focusing the needs according to new technologies. Multimedia content has become a central part of the flow of information in our daily life. This reflects the necessity of having multimedia search engines, as well as knowing the real tasks that it must comply. Through this analysis, it is shown that there are not many search engines that can perform content searches. The area of research of multimedia search engines of new generation is a multidisciplinary area that’s in constant growth, generating tools that satisfy the different needs of new generation systems.

Computer vision is an important task in robotics applications. This work proposes an approach for autonomous mobile robot navigation using the integration of the template-matching filters for obstacle detection and the evolutionary artificial potential field method for path planning. The recognition system employs a digital camera to sense the environment of a mobile robot. The captured scene is processed by a bank of space variant filters in order to find the obstacles and a feasible area for the robot navigation. The path planning employs evolutionary artificial potential fields to derive optimal potential field functions using evolutionary computation. Simulation results to validate the analysis and implementation are provided; they were specifically made to show the effectiveness and the efficiency of the proposal.

In the computer world, the consumption and generation of multimedia content are in constant growth due to the popularization of mobile devices and new communication technologies. Retrieve information from multimedia content to describe Mexican buildings is a challenging problem. Our objective is to determine patterns related to three building eras (Pre-Hispanic, colonial and modern). For this purpose, existing recognition systems need to process a plenty of videos and images. The automatic learning systems trains the recognition capability with a semantic-annotated database. We built the database taking into account high-level feature concepts, user knowledge and experience. The annotations helps correlating context and content to understand the data on multimedia files. Without a method, the user needs a super mind to remember all and registry this data manually. This article presents a methodology for a quick images annotation using a graphical interface and intuitive controls. Emphasizing in the most two important features: time-consuming during annotations task and the quality of selected images. Though, we only classify images by its era and its quality. Finally, we obtain a dataset of Mexican buildings preserving the contextual information with semantic-annotations for training and test of buildings recognition systems. Therefore, research on content low-level descriptors is other possible use for this dataset.

In this paper, an overlapped sub-block gray-level average method for contrast enhancement is presented. The digital image correction of uneven illumination under microscope transmittance is a problem in image processing, also sometimes the image in the dark place need to correct the uneven problem. A new correction method was proposed based on the mask method and sub-blocks gray-level average method because Traditional mask method and background fitting method are restricted due to application scenarios, and the corrected image brightness is low by using background fitting method, so it has some limitations of the application. In this paper, we introduce a new method called AOSCE for image contrast enhancement. The image is divided into many sub-blocks which are overlapped, calculate the average gray-level of the whole image as M and the calculate the average gray-level of each one as mi, next for each block it can get d = mi - m, each block minus d to get a new image, and then get the minimum gray-level of each block into a matrix DD to get the background, and use bilinearity to get the same scale of the image. over fitting the image in matlab in order to get smoother image, then minus the background to get the contrast enhancement image.

A locally-adaptive algorithm for speech enhancement based on local spectral regularization is presented. The algorithm is able to retrieve a clean speech signal from a noisy signal using locally-adaptive signal processing. The proposed algorithm is able to increase the quality of a noisy signal in terms of objective metrics. Computer simulation results obtained with the proposed algorithm are presented and discussed in processing speech signals corrupted with additive noise.

In order to study the learning behaviors of college students, we need to identify students with the monitoring videos in the context of college classroom. We analyze the main challenges of face recognition under classroom conditions, and propose a face recognition method via combining multi-feature with alignment preprocessing. Obviously, the more identification photos per student may improve the recognition accuracy and the computational complexity simultaneously. Aiming at the practical use, we not only study on the accuracy but also the efficiency of the proposed method. We use the practical classroom videos and standard face databases to explore the best feature fusion strategies and prove the universality of the method.

The generation of light containing large degrees of orbital angular momentum (OAM) has recently been demon- strated in both the classical and quantum regimes. Since there is no fundamental limit to how many quanta of OAM a single photon can carry, optical states with an arbitrarily high difference in this quantum number may, in principle, be entangled. This opens the door to investigations into high-dimensional entanglement shared between states in superpositions of nonzero OAM. Additionally, making use of non-zero OAM states can allow for a dramatic increase in the amount of information carried by a single photon, thus increasing the information capacity of a communication channel. In practice, however, it is difficult to differentiate between states with high OAM numbers with high precision. Here we investigate the ability of deep neural networks to differentiate between states that contain large values of OAM. We show that such networks may be used to differentiate be- tween nearby OAM states that contain realistic amounts of noise, with OAM values of up to 100. Additionally, we examine how the classification accuracy scales with the signal-to-noise ratio of images that are used to train the network, as well as those being tested. Finally, we demonstrate the simultaneous classification of < 100 OAM states with greater than 70 % accuracy. We intend to verify our system with experimentally-produced classi- cal OAM states, as well as investigate possibilities that would allow this technique to work in the few-photon quantum regime.

Considering the change of optical information on material surface, this paper proposes a useful notion called pixel-level optical constants (POC). Through Fresnel equations, traditional optical constants (refractive index n and extinction coefficient k ) can reflect photoelectric characteristics on material surface. Combining with Mueller calculus in polarization optics, POC can describe the distrbution of photoelectric characteristics on material surface. POC is mainly calculated by the decomposition of Mueller matrix which includes Fresnel amplitude, ratio of two orthogonal reflection coefficient component P and variation of phase difference between incident light and reflected light Δ . With the regularity of polarized light and the statistics of Mueller matrices, optical characteristics can be detailed to each pixel in POC, which will independently show the distribution of polarization characteristics on material surface. And it can also be approximately averaged to obtain traditional optical constants. So POC is significant to optical researches on material surface.

Gemological Institute of America (GIA) has developed a diamond color measurement instrument that can provide accurate and reproducible color measurement results. The instrument uses uniform illumination by a daylight-approximating light source; observations from a high-resolution color-camera with nearly zero-distortion bi-telecentric lens, and image processing to calculate color parameters of diamonds. Experiments show the instrument can provide reproducible color measurement results and also identify subtle color differences in diamonds with high sensitivity. The experimental setup of the prototype instrument and the image processing method for calculating diamond color parameters are presented in this report.

In the field of pedagogy or educational psychology, emotions are treated as very important factors, which are closely associated with cognitive processes. Hence, it is meaningful for teachers to analyze students’ emotions in classrooms, thus adjusting their teaching activities and improving students ’ individual development. To provide a benchmark for different expression recognition algorithms, a large collection of training and test data in classroom environment has become an acute problem that needs to be resolved. In this paper, we present a multimodal spontaneous database in real learning environment. To collect the data, students watched seven kinds of teaching videos and were simultaneously filmed by a camera. Trained coders made one of the five learning expression labels for each image sequence extracted from the captured videos. This subset consists of 554 multimodal spontaneous expression image sequences (22,160 frames) recorded in real classrooms. There are four main advantages in this database. 1) Due to recorded in the real classroom environment, viewer’s distance from the camera and the lighting of the database varies considerably between image sequences. 2) All the data presented are natural spontaneous responses to teaching videos. 3) The multimodal database also contains nonverbal behavior including eye movement, head posture and gestures to infer a student ’ s affective state during the courses. 4) In the video sequences, there are different kinds of temporal activation patterns. In addition, we have demonstrated the labels for the image sequences are in high reliability through Cronbach's alpha method.

According to the different degree distortion of lens array used in machine visual detection and high precision three-dimensional (3D) reconstruction, this paper proposes a combined radial and tangential distortion model-based for lens array distortion correction. A lens follows the pinhole model if and only if the projection of every line in space onto the lens is a line. In this paper, we propose straight lines fast correction algorithm to correct lens distortion to an estimated average error less than 1 pixel. In the algorithm, we adopt automatically detecting chessboard corners and linear interconnected algorithm to weaken human disturbance. Experimental results indicate that the algorithm can promote the precision and strengthen the robustness, meanwhile, greatly reduce the running time.

A generalized amplitude-phase retrieval algorithm (GAPRA) attack on ‘double images encryption method with resistance against the special attack based on an asymmetric algorithm’ (DIEM) is presented in this paper. The analysis shows that the DIEM is a cascaded cryptosystem, which consist of a joint transform correlator architecture and a phasetruncated Fourier transform scheme. A GAPRA attack is proposed and the potential risk of the cascaded cryptosystems is discussed. By using our method, an attacker could crack high-quality results of the plaintexts. A set of simulation results demonstrate the validity and feasibility of the proposed method.

Photopolymers are classical holographic recording materials. Recently their chemical composition and the fabrication techniques have been optimized for many new applications such as interconnectors, solar concentrations, 2-D photonic structures, or wave-guides. Their potential usefulness has been drastically increased by the introduction of dispersed liquid crystal molecules; these components can be concentrated in the non-exposed zones of the material by a photopolymerization induced phase separation process (PIPS). Therefore, by combining polymer and dispersed liquid crystal (PDLC) has emerged as a new composite material for switchable diffractive optical elements (DOEs). Parallel to the material advances some techniques have been proposed to record very low spatial frequencies DOE’s. Different researchers have reported proposes to record DOE like fork gratings, photonics structures, lenses, sinusoidal, blazed or fork gratings. In this work we have studied the behavior of a PDLC material to record DOE’s with different spatial periods: from 1 μm, using holographic technique, to more than 200 μm, Liquid Cristal on Silicon (LCoS) display working in mostly amplitude mode as a master. Due to the improvement in the spatial light modulation technology and the pixel miniaturization, this technique permits us store gratings with spatial frequencies until few microns. Additionally, this technology permits us an accurate and dynamic control of the phase and the amplitude of the recording beam. In particular, for our case, to generate the blazed gratings, we use an LCoS-Pluto provided by Holoeye with a resolution of 1920x1080 (HDTV) pixels and a pixel size of 7.7x7.7 m².

When timescale of the molecule kinetics faster than the bin time of millisecond order, the commercial single- molecule fluorescence resonance energy transfer (smFRET) data analysis tools may not clearly separate different states. We proposed a novel method to obtain the analysis result from smFRET raw data in microsecond scale. We introduced Akaike information criterion and non-stationarity measure in the fitting procedure to give an objective estimate about the number of states and populations. The results were used as initial values to make parameter estimation about equilibrium populations and transition rates from the photon trajectories based on an iterative optimizing procedure.

In this work we present a high pixel count color holographic registration system that is designed to provide 3D holographic content of real-world large objects. Captured data is dedicated for holographic displays with a wide-viewing angle. The registration in color is realized by means of sequential recording with the use of three RGB laser light sources. The applied Fourier configuration of capture system gives large viewing angle and an optimal coverage of the detector resolution. Moreover, it enables to filter out zero order and twin image. In this work the captured Fourier holograms are transformed to general Fresnel type that is more suitable for 3D holographic displays. High resolution and large pixel count of holographic data and its spatial continuity is achieved through synthetic aperture concept with camera scanning and subpixel correlation based stitching. This grants an access to many tools of numerical hologram processing e.g. continuous viewing angle adjustment, and control of 3D image position and size. In this paper the properties of 1D synthetic aperture (60000 x 2500 pixels) are investigated. Each of the RGB 1D SA holograms is composed of 71 frames, which after stitching result in approx. 150 Megapixel hologram pixel count and 12° angular field of view. In experimental part high quality numerical reconstructions for each type of the hologram are shown. Moreover, the captured holograms are used for generation of hybrid hologram that is assembled from a set of RGB holograms of different color statues of height below 20 cm. In the final experiment this hybrid hologram as well as RGB hologram of a single object are reconstructed in the color holographic display.

Information rate that can be transferred over a given bandwidth is limited by the information theory. Capacity depends on many factors such as the signal to noise ratio (SNR), channel state information (CSI) and the spatial correlation in the propagation environment. It is very important to increase spectral efficiency in order to meet the growing demand for wireless services. Thus, Multiple input multiple output (MIMO) technology has been developed and applied in most of the wireless standards and it has been very successful in increasing capacity and reliability. As the demand is still increasing, attention now is shifting towards large scale multiple input multiple output (MIMO) which has a potential of bringing orders of magnitude of improvement in spectral and energy efficiency. It has been shown that users channels decorrelate after increasing the number of antennas. As a result, inter-user interference can be avoided since energy can be focused on precise directions. This paper investigates the limits of channel capacity for large scale MIMO. We study the relation between spectral efficiency and the number of antenna N. We use time division duplex (TDD) system in order to obtain CSI using training sequence in the uplink. The same CSI is used for the downlink because the channel is reciprocal. Spectral efficiency is measured for channel model that account for small scale fading while ignoring the effect of large scale fading. It is shown the spectral efficiency can be improved significantly when compared to single antenna systems in ideal circumstances.

The model of Mueller-matrix description of mechanisms of optical anisotropy that typical for polycrystalline layers of the histological sections of biological tissues and fluids - optical activity, birefringence, as well as linear and circular dichroism - is suggested. Within the statistical analysis distributions quantities of linear and circular birefringence and dichroism the objective criteria of differentiation of myocardium histological sections (determining the cause of death); films of blood plasma (liver pathology); peritoneal fluid (endometriosis of tissues of women reproductive sphere); urine (kidney disease) were determined. From the point of view of probative medicine the operational characteristics (sensitivity, specificity and accuracy) of the method of Mueller-matrix reconstruction of optical anisotropy parameters were found.

A new azimuthally stable polarimetric method for processing of microscopic images of optically anisotropic structures of different biological layers histological sections is proposed. A new model of phase anisotropy definition of biological tissues by using superposition of Mueller matrices of linear birefringence and optical activity is proposed. The matrix element M44 has been chosen as the main information parameter, which value is independent of rotation angle of both sample and probing beam polarization plane.

The high demand on the wireless networks and the need for higher data rates are the motivation to develop new technologies. Recently, the idea of using large-scale MIMO systems has grabbed great attention from the researchers due to its high spectral and energy efficiency. In this paper, we analyze the UL channel estimation error using large number of antennas in the base station where the UL channel is based on predefined pilot signal. By making a comparison between the identified UL pilot signal and the received UL signal we can get the realization of the channel. We choose to deal with one cell scenario where the effect of inter-cell interference is eliminated for the sake of studying simple approach. While the number of antennas is very large in the base station side, we choose to have one antennal in the user terminal side. We choose to have two models to generate the channel covariance matrix includes one-ring model and exponential correlation model. Figures of channel estimation error are generated where the performance of the mean square error MSE per antenna is presented as a function signal to noise ratio SNR. The simulation results show that the higher the SNR the better the performance. Furthermore, the affect of the pilot length on the channel estimation error is studied where two different covariance models are used to see the impact of the two cases. In the two cases, the increase of the pilot length has improved the estimation accuracy.

Scale estimation of objects is a challenging problem in image processing. This work presents a novel method to detect and estimate the scaling factor of a target in an observed scene corrupted with additive noise and clutter. Given a set of available views of the target the proposed method is able to detect the target and estimate its scaling factor using a template matched filters and a scale pyramidal representation. The performance of the proposed method is evaluated in synthetic and real-life scenes in different pattern recognition applications. The obtained results are characterized in terms of objective metrics.

We propose an optical correlation algorithm for reconstructing the phase skeleton of complex optical fields from the measured two-dimensional intensity distribution. The essence of the algorithm consists in location of the saddle points of the intensity distribution and connecting such points into nets by the lines of intensity gradient that are closely associated with the equi-phase lines of the field. This algorithm provides a new partial solution to the inverse problem in optics commonly referred to as the phase problem.

The paper presents principal approaches to diagnosing the structure forming skeleton of the complex optical field. It is shown that intensity distribution smoothing and bicubic spline simulation allow to bring much closer the solution of the phase problem of localization speckle-field special points.

The paper presents principal approaches to diagnosing the structure forming skeleton of the complex optical field. An analysis of optical field singularity algorithms depending on intensity discretization and image resolution has been carried out. An optimal approach is chosen, which allows to bring much closer the solution of the phase problem of localization speckle-field special points. The use of a “window” 2D Hilbert transform for reconstruction of the phase distribution of the intensity of a speckle field is proposed. It is shown that the advantage of this approach consists in the invariance of a phase map to a change of the position of the kernel of transformation and in a possibility to reconstruct the structure-forming elements of the skeleton of an optical field, including singular points and saddle points. We demonstrate the possibility to reconstruct the equi-phase lines within a narrow confidence interval, and introduce an additional algorithm for solving the phase problem for random 2D intensity distributions.

The interaction of two mutually orthogonal linearly polarized waves in the incidence plane, where the modulation of polarization and the modulation of the energy volume density occur simultaneously in the observation plane is considered. The spatial modulation of polarization in the observation plane forms the spatial modulation of the energy volume density, which changes the velocity of the particle’s motion according to the coherence characteristics of superposing fields and the resulting optical force that causes the motion of tested particles of micrometer range size. Peculiarities of particle’s motion in a spatial periodically modulated polarized field are determined by coherent properties of interacting optical fields.

The proposed paper investigates the influence of a coherence degree of superposing mutually orthogonal linearly−polarized waves on the peculiarities of nanosize range particle motion in the inhomogeneously polarized optical field and field of the averaged values of the Poynting vector. In this case the depth of the energy volume density modulation essentially depends on the degree of coherence of interacting waves. The way of monitoring particles of the Rayleigh light scattering mechanism in the energy inhomogeneous optical field is proposed for investigation. The increase of spin flows influence on optical fields studying is analyzed. The possibility of controlling particles of different properties and characteristics becomes possible due to the intrinsic optical flows action.

A reliable method for three-dimensional digitization of human faces based on the fringe projection technique is presented. The proposed method employs robust fringe analysis algorithms for robust phase computation. The quality of the resultant 3D face model is characterized in terms of accuracy of surface computation using objective metrics. We present experimental results obtained with real and synthetic laboratory objects. The potential of this method to be used in the field of face recognition is discussed.

Infrared polarization imaging is a new kind of infrared detection technology developed in recent ten years. Different from the traditional detection method of infrared imaging, infrared polarization imaging can not only obtain infrared radiation intensity information of targets, but also obtain the infrared radiation polarization information. So the polarization of the target scene is the physical basis of infrared polarization imaging detection. On the basis of the research about infrared polarization imaging theory, the characteristics of long-wave infrared polarization detection was analyzed in this paper. Firstly, the paper studied long-wave infrared polarization state and interaction effect which coming from the spontaneous emission of target and environment, then designed the analysis experiment about long-wave infrared polarization characteristics that coming from spontaneous radiation, further and verified the forming mechanism of long wave infrared polarization. Through the several experiments that the long wave polarization information of different material objects being measured, a physical phenomenon was found that with the long-wave thermal radiation transmitting form high temperature object to low temperature object, the polarization characteristics transfer process had been happened at the same time, and the degree of this transfer was associated with the material and self-temperature of the objects.

A feature extraction-based classification method is proposed in this paper for verifying the capability of human’s neck in target tracking. Here, the target moves in predefined trajectory patterns in three difficulty levels. Dataset used for each pattern is obtained from two groups of people, one with whiplash associated disorder (WAD) and asymptomatic group, who behave in both sincere and feign manner. The aim is to verify the WAD group from asymptomatic one and also to discriminate the sincere behavior from the feigned one. Sparse and low-rank feature extraction is proposed to extract the most informative feature from training samples and then each sample is classified into the group which has the highest correlation coefficient with. The classification results are improved by fusing the results of the three patterns.