WorldWideScience

Sample records for nonlinear spectral imaging

  1. Nonlinear spectral imaging of biological tissues

    Science.gov (United States)

    Palero, J. A.

    2007-07-01

    The work presented in this thesis demonstrates live high resolution 3D imaging of tissue in its native state and environment. The nonlinear interaction between focussed femtosecond light pulses and the biological tissue results in the emission of natural autofluorescence and second-harmonic signal. Because biological intrinsic emission is generally very weak and extends from the ultraviolet to the visible spectral range, a broad-spectral range and high sensitivity 3D spectral imaging system is developed. Imaging the spectral characteristics of the biological intrinsic emission reveals the structure and biochemistry of the cells and extra-cellular components. By using different methods in visualizing the spectral images, discrimination between different tissue structures is achieved without the use of any stain or fluorescent label. For instance, RGB real color spectral images of the intrinsic emission of mouse skin tissues show blue cells, green hair follicles, and purple collagen fibers. The color signature of each tissue component is directly related to its characteristic emission spectrum. The results of this study show that skin tissue nonlinear intrinsic emission is mainly due to the autofluorescence of reduced nicotinamide adenine dinucleotide (phosphate), flavins, keratin, melanin, phospholipids, elastin and collagen and nonlinear Raman scattering and second-harmonic generation in Type I collagen. In vivo time-lapse spectral imaging is implemented to study metabolic changes in epidermal cells in tissues. Optical scattering in tissues, a key factor in determining the maximum achievable imaging depth, is also investigated in this work.

  2. Nonlinear spectral imaging of biological tissues

    NARCIS (Netherlands)

    Palero, J.A.

    2007-01-01

    The work presented in this thesis demonstrates live high resolution 3D imaging of tissue in its native state and environment. The nonlinear interaction between focussed femtosecond light pulses and the biological tissue results in the emission of natural autofluorescence and second-harmonic signal.

  3. Nonlinear spectral imaging of biological tissues

    NARCIS (Netherlands)

    Palero, J.A.

    2007-01-01

    The work presented in this thesis demonstrates live high resolution 3D imaging of tissue in its native state and environment. The nonlinear interaction between focussed femtosecond light pulses and the biological tissue results in the emission of natural autofluorescence and second-harmonic signal.

  4. Nonlinear spectral unmixing of hyperspectral images using Gaussian processes

    CERN Document Server

    Altmann, Yoann; McLaughlin, Steve; Tourneret, Jean-Yves

    2012-01-01

    This paper presents an unsupervised algorithm for nonlinear unmixing of hyperspectral images. The proposed model assumes that the pixel reflectances result from a nonlinear function of the abundance vectors associated with the pure spectral components. We assume that the spectral signatures of the pure components and the nonlinear function are unknown. The first step of the proposed method consists of the Bayesian estimation of the abundance vectors for all the image pixels and the nonlinear function relating the abundance vectors to the observations. The endmembers are subsequently estimated using Gaussian process regression. The performance of the unmixing strategy is evaluated with simulations conducted on synthetic and real data.

  5. Molecular Histopathology by Spectrally Reconstructed Nonlinear Interferometric Vibrational Imaging

    Science.gov (United States)

    Chowdary, Praveen D.; Jiang, Zhi; Chaney, Eric J.; Benalcazar, Wladimir A.; Marks, Daniel L.; Gruebele, Martin; Boppart, Stephen A.

    2011-01-01

    Sensitive assays for rapid quantitative analysis of histologic sections, resected tissue specimens, or in situ tissue are highly desired for early disease diagnosis. Stained histopathology is the gold standard but remains a subjective practice on processed tissue taking from hours to days. We describe a microscopy technique that obtains a sensitive and accurate color-coded image from intrinsic molecular markers. Spectrally reconstructed nonlinear interferometric vibrational imaging can differentiate cancer versus normal tissue sections with greater than 99% confidence interval in a preclinical rat breast cancer model and define cancer boundaries to ±100 μm with greater than 99% confidence interval, using fresh unstained tissue sections imaged in less than 5 minutes. By optimizing optical sources and beam delivery, this technique can potentially enable real-time point-of-care optical molecular imaging and diagnosis. PMID:21098699

  6. In vivo nonlinear spectral imaging in mouse skin

    NARCIS (Netherlands)

    J.A. Palero (Jonathan); H.S. de Bruijn (Riette); A. van der Ploeg-van den Heuvel (Angélique); H.J.C.M. Sterenborg (Dick); H.C. Gerritsen (Hans)

    2006-01-01

    textabstractWe report on two-photon autofluorescence and second harmonic spectral imaging of live mouse tissues. The use of a high sensitivity detector and ultraviolet optics allowed us to record razor-sharp deep-tissue spectral images of weak autofluorescence and short-wavelength second harmonic

  7. Interferometric and nonlinear-optical spectral-imaging techniques for outer space and live cells

    Science.gov (United States)

    Itoh, Kazuyoshi

    2015-12-01

    Multidimensional signals such as the spectral images allow us to have deeper insights into the natures of objects. In this paper the spectral imaging techniques that are based on optical interferometry and nonlinear optics are presented. The interferometric imaging technique is based on the unified theory of Van Cittert-Zernike and Wiener-Khintchine theorems and allows us to retrieve a spectral image of an object in the far zone from the 3D spatial coherence function. The retrieval principle is explained using a very simple object. The promising applications to space interferometers for astronomy that are currently in progress will also be briefly touched on. An interesting extension of interferometric spectral imaging is a 3D and spectral imaging technique that records 4D information of objects where the 3D and spectral information is retrieved from the cross-spectral density function of optical field. The 3D imaging is realized via the numerical inverse propagation of the cross-spectral density. A few techniques suggested recently are introduced. The nonlinear optical technique that utilizes stimulated Raman scattering (SRS) for spectral imaging of biomedical targets is presented lastly. The strong signals of SRS permit us to get vibrational information of molecules in the live cell or tissue in real time. The vibrational information of unstained or unlabeled molecules is crucial especially for medical applications. The 3D information due to the optical nonlinearity is also the attractive feature of SRS spectral microscopy.

  8. NONLINEAR SPECTRAL IMAGING OF ELASTIC CARTILAGE IN RABBIT EARS

    Directory of Open Access Journals (Sweden)

    JING CHEN

    2013-07-01

    Full Text Available Elastic cartilage in the rabbit external ear is an important animal model with attractive potential value for researching the physiological and pathological states of cartilages especially during wound healing. In this work, nonlinear optical microscopy based on two-photon excited fluorescence and second harmonic generation were employed for imaging and quantifying the intact elastic cartilage. The morphology and distribution of main components in elastic cartilage including cartilage cells, collagen and elastic fibers were clearly observed from the high-resolution two-dimensional nonlinear optical images. The areas of cell nuclei, a parameter related to the pathological changes of normal or abnormal elastic cartilage, can be easily quantified. Moreover, the three-dimensional structure of chondrocytes and matrix were displayed by constructing three-dimensional image of cartilage tissue. At last, the emission spectra from cartilage were obtained and analyzed. We found that the different ratio of collagen over elastic fibers can be used to locate the observed position in the elastic cartilage. The redox ratio based on the ratio of nicotinamide adenine dinucleotide (NADH over flavin adenine dinucleotide (FAD fluorescence can also be calculated to analyze the metabolic state of chondrocytes in different regions. Our results demonstrated that this technique has the potential to provide more accurate and comprehensive information for the physiological states of elastic cartilage.

  9. Direct optical imaging of graphene in vitro by nonlinear femtosecond laser spectral reshaping.

    Science.gov (United States)

    Li, Baolei; Cheng, Yingwen; Liu, Jie; Yi, Congwen; Brown, April S; Yuan, Hsiangkuo; Vo-Dinh, Tuan; Fischer, Martin C; Warren, Warren S

    2012-11-14

    Nonlinear optical microscopy, based on femtosecond laser spectral reshaping, characterized and imaged graphene samples made from different methods, both on slides and in a biological environment. This technique clearly discriminates between graphene flakes with different numbers of layers and reveals the distinct nonlinear optical properties of reduced graphene oxide as compared to mechanically exfoliated or chemical vapor deposition grown graphene. The nonlinearity makes it applicable to scattering samples (such as tissue) as opposed to previous methods, such as transmission. This was demonstrated by high-resolution imaging of breast cancer cells incubated with graphene flakes.

  10. Monitoring the metabolic state of fungal hyphae and the presence of melanin by nonlinear spectral imaging

    NARCIS (Netherlands)

    Knaus, H.; Blab, G.; Agronskaia, A.V.; van den Heuvel, D.J.; Gerritsen, H.C.; Wösten, H.A.B.

    2013-01-01

    Label-free nonlinear spectral imaging microscopy (NLSM) records two-photon-excited fluorescence emission spectra of endogenous fluorophores within the specimen. Here, NLSM is introduced as a novel, minimally invasive method to analyze the metabolic state of fungal hyphae by monitoring the autofluore

  11. Observation of spectral self-imaging by nonlinear parabolic cross-phase modulation.

    Science.gov (United States)

    Lei, Lei; Huh, Jeonghyun; Cortés, Luis Romero; Maram, Reza; Wetzel, Benjamin; Duchesne, David; Morandotti, Roberto; Azaña, José

    2015-11-15

    We report an experimental demonstration of spectral self-imaging on a periodic frequency comb induced by a nonlinear all-optical process, i.e., parabolic cross-phase modulation in a highly nonlinear fiber. The comb free spectral range is reconfigured by simply tuning the temporal period of the pump parabolic pulse train. In particular, undistorted FSR divisions by factors of 2 and 3 are successfully performed on a 10 GHz frequency comb, realizing new frequency combs with an FSR of 5 and 3.3 GHz, respectively. The pump power requirement associated to the SSI phenomena is also shown to be significantly relaxed by the use of dark parabolic pulses.

  12. In vivo monitoring of protein-bound and free NADH during ischemia by nonlinear spectral imaging microscopy

    NARCIS (Netherlands)

    J.A. Palero (Jonathan); A.N. Bader (Arjen); H.S. de Bruijn (Riette); A.V.D.P. van den Heuvel (Angélique); H.J.C.M. Sterenborg (Dick); H.C. Gerritsen (Hans)

    2011-01-01

    textabstractNonlinear spectral imaging microscopy (NSIM) allows simultaneous morphological and spectroscopic investigation of intercellular events within living animals. In this study we used NSIM for in vivo timelapse in-depth spectral imaging and monitoring of protein-bound and free reduced nicoti

  13. In vivo monitoring of protein-bound and free NADH during ischemia by nonlinear spectral imaging microscopy

    NARCIS (Netherlands)

    Palero, J.A.; Bader, A.N.; de Bruijn, H.S.; van der Ploeg van den Heuvel, A.; Sterenborg, H.J.C.M.; Gerritsen, H.C.

    2011-01-01

    Nonlinear spectral imaging microscopy (NSIM) allows simultaneous morphological and spectroscopic investigation of intercellular events within living animals. In this study we used NSIM for in vivo time-lapse in-depth spectral imaging and monitoring of protein-bound and free reduced nicotinamide aden

  14. Parallel implementation of linear and nonlinear spectral unmixing of remotely sensed hyperspectral images

    Science.gov (United States)

    Plaza, Antonio; Plaza, Javier

    2011-11-01

    Hyperspectral unmixing is a very important task for remotely sensed hyperspectral data exploitation. It addresses the (possibly) mixed nature of pixels collected by instruments for Earth observation, which are due to several phenomena including limited spatial resolution, presence of mixing effects at different scales, etc. Spectral unmixing involves the separation of a mixed pixel spectrum into its pure component spectra (called endmembers) and the estimation of the proportion (abundance) of endmember in the pixel. Two models have been widely used in the literature in order to address the mixture problem in hyperspectral data. The linear model assumes that the endmember substances are sitting side-by-side within the field of view of the imaging instrument. On the other hand, the nonlinear mixture model assumes nonlinear interactions between endmember substances. Both techniques can be computationally expensive, in particular, for high-dimensional hyperspectral data sets. In this paper, we develop and compare parallel implementations of linear and nonlinear unmixing techniques for remotely sensed hyperspectral data. For the linear model, we adopt a parallel unsupervised processing chain made up of two steps: i) identification of pure spectral materials or endmembers, and ii) estimation of the abundance of each endmember in each pixel of the scene. For the nonlinear model, we adopt a supervised procedure based on the training of a parallel multi-layer perceptron neural network using intelligently selected training samples also derived in parallel fashion. The compared techniques are experimentally validated using hyperspectral data collected at different altitudes over a so-called Dehesa (semi-arid environment) in Extremadura, Spain, and evaluated in terms of computational performance using high performance computing systems such as commodity Beowulf clusters.

  15. A BVMF-B algorithm for nonconvex nonlinear regularized decomposition of spectral x-ray projection images

    Science.gov (United States)

    Pham, Mai Quyen; Ducros, Nicolas; Nicolas, Barbara

    2017-03-01

    Spectral computed tomography (CT) exploits the measurements obtained by a photon counting detector to reconstruct the chemical composition of an object. In particular, spectral CT has shown a very good ability to image K-edge contrast agent. Spectral CT is an inverse problem that can be addressed solving two subproblems, namely the basis material decomposition (BMD) problem and the tomographic reconstruction problem. In this work, we focus on the BMD problem, which is ill-posed and nonlinear. The BDM problem is classically either linearized, which enables reconstruction based on compressed sensing methods, or nonlinearly solved with no explicit regularization scheme. In a previous communication, we proposed a nonlinear regularized Gauss-Newton (GN) algorithm.1 However, this algorithm can only be applied to convex regularization functionals. In particular, the lp (p thorax phantom made of soft tissue, bone and gadolinium, which is scanned with a 90-kV x-ray tube and a 3-bin photon counting detector.

  16. Nonlinear spectral imaging of human hypertrophic scar based on two-photon excited fluorescence and second-harmonic generation.

    Science.gov (United States)

    Chen, G; Chen, J; Zhuo, S; Xiong, S; Zeng, H; Jiang, X; Chen, R; Xie, S

    2009-07-01

    A noninvasive method using microscopy and spectroscopy for analysing the morphology of collagen and elastin and their biochemical variations in skin tissue will enable better understanding of the pathophysiology of hypertrophic scars and facilitate improved clinical management and treatment of this disease. To obtain simultaneously microscopic images and spectra of collagen and elastin fibres in ex vivo skin tissues (normal skin and hypertrophic scar) using a nonlinear spectral imaging method, and to compare the morphological structure and spectral characteristics of collagen and elastin fibres in hypertrophic scar tissues with those of normal skin, to determine whether this approach has potential for in vivo assessment of the pathophysiology of human hypertrophic scars and for monitoring treatment responses as well as for tracking the process of development of hypertrophic scars in clinic. Ex vivo human skin specimens obtained from six patients aged from 10 to 50 years old who were undergoing skin plastic surgery were examined. Five patients had hypertrophic scar lesions and one patient had no scar lesion before we obtained his skin specimen. A total of 30 tissue section samples of 30 mum thickness were analysed by the use of a nonlinear spectral imaging system consisting of a femtosecond excitation light source, a high-throughput scanning inverted microscope, and a spectral imaging detection system. The high-contrast and high-resolution second harmonic generation (SHG) images of collagen and two-photon excited fluorescence (TPEF) images of elastin fibres in hypertrophic scar tissues and normal skin were acquired using the extracting channel tool of the system. The emission spectra were analysed using the image-guided spectral analysis method. The depth-dependent decay constant of the SHG signal and the image texture characteristics of hypertrophic scar tissue and normal skin were used to quantitatively assess the amount, distribution and orientation of their

  17. Nonlinear Bayesian Algorithms for Gas Plume Detection and Estimation from Hyper-spectral Thermal Image Data

    Energy Technology Data Exchange (ETDEWEB)

    Heasler, Patrick G.; Posse, Christian; Hylden, Jeff L.; Anderson, Kevin K.

    2007-06-13

    This paper presents a nonlinear Bayesian regression algorithm for the purpose of detecting and estimating gas plume content from hyper-spectral data. Remote sensing data, by its very nature, is collected under less controlled conditions than laboratory data. As a result, the physics-based model that is used to describe the relationship between the observed remotesensing spectra, and the terrestrial (or atmospheric) parameters that we desire to estimate, is typically littered with many unknown "nuisance" parameters (parameters that we are not interested in estimating, but also appear in the model). Bayesian methods are well-suited for this context as they automatically incorporate the uncertainties associated with all nuisance parameters into the error estimates of the parameters of interest. The nonlinear Bayesian regression methodology is illustrated on realistic simulated data from a three-layer model for longwave infrared (LWIR) measurements from a passive instrument. This shows that this approach should permit more accurate estimation as well as a more reasonable description of estimate uncertainty.

  18. Optical multiple-image encryption in diffractive-imaging-based scheme using spectral fusion and nonlinear operation.

    Science.gov (United States)

    Qin, Yi; Gong, Qiong; Wang, Zhipeng; Wang, Hongjuan

    2016-11-14

    We report a new method for multiple-image encryption in diffractive-imaging-based encryption (DIBE) scheme. The discrete cosine transformation (DCT) spectra of the primary images are extracted, compacted and then nonlinear-transformed before being sent to the DIBE, where they are encoded into a single intensity pattern. With the help of a suggested phase retrieval algorithm, the original images can be recovered with high quality. Furthermore, due to the introduction of the nonlinear operation, the proposal is demonstrated to be robust to the currently available cryptographic attacks. The proposal probes a new way for multiple-image encryption in DIBE, and its effectiveness and feasibility have been supported by numerical simulations.

  19. Spectrally resolved cathodoluminescence imaging study of periodic [001]/[00-1] GaAs structures for nonlinear optical conversion

    Energy Technology Data Exchange (ETDEWEB)

    Hortelano, V.; Martinez, O.; Jimenez, J. [GdS Optronlab., Univ. de Valladolid, Paseo de Belen 1, 47011 Valladolid (Spain); Lynch, C.; Snure, M.; Bliss, D. [Air Force Research Laboratory, Sensors Directorate, Hanscom AFB, MA 01731 (United States)

    2012-07-15

    Orientation patterned (OP)-GaAs crystals are very promising as nonlinear optical materials. They are suitable for mid-infrared and terahertz laser sources, by frequency conversion of shorter wavelength pump sources. OP-GaAs crystals must contain low concentrations of defects and must be homogeneous to reduce fluctuations, in the refractive index and the concomitant optical propagation losses. Understanding of the defects with electrooptic signature is crucial to improve the growth conditions for reducing their presence. Spectrally resolved cathodoluminescence imaging is used to study the main defects and how they are distributed throughout the OP-GaAs crystal (copyright 2012 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim) (orig.)

  20. 高光谱图像非线性解混方法的研究进展%Advances in Nonlinear Spectral Unmixing of Hyperspectral Images

    Institute of Scientific and Technical Information of China (English)

    唐晓燕; 高昆; 倪国强

    2013-01-01

    由于空间分辨率的限制,高光谱遥感图像中存在大量混合像元,对混合像元的解混是实现地物精确分类和识别的前提.与传统的线性解混方法相比,非线性解混方法在寻找组成混合像元的端元以及每个端元的丰度时具有较高的精度.分析了光谱非线性混合的原理,总结了近年来提出的非线性解混算法,重点对双线性模型、神经网络、基于核函数的非线性解混算法以及基于流形学习的非线性解混算法进行了介绍和分析.最后总结了混合像元非线性解混未来发展的趋势.%Due to the limitation of spatial resolution,there are lots of mixed pixels in spaceborne hyperspectral images.Spectral unmixing of hyperspectral images is an important premise for accurate terrain classification and identification.Compared with traditional spectral unmixing techniques based on the linear mixing model,nonlinear spectral unmixing techniques has better performance in finding endmembers and their abundances.The principle of nonlinear spectral mixture is analysed,and nonlinear unmixing algorithms increased in recent years are summarized.This paper emphatically introduces bilinear model,neural networks,nonlinear spectral decomposing based on kernel function and manifold learning.Some future directions of research are introduced.

  1. Snapshot spectral imaging system

    Science.gov (United States)

    Arnold, Thomas; De Biasio, Martin; McGunnigle, Gerald; Leitner, Raimund

    2010-02-01

    Spectral imaging is the combination of spectroscopy and imaging. These fields are well developed and are used intensively in many application fields including industry and the life sciences. The classical approach to acquire hyper-spectral data is to sequentially scan a sample in space or wavelength. These acquisition methods are time consuming because only two spatial dimensions, or one spatial and the spectral dimension, can be acquired simultaneously. With a computed tomography imaging spectrometer (CTIS) it is possible to acquire two spatial dimensions and a spectral dimension during a single integration time, without scanning either spatial or spectral dimensions. This makes it possible to acquire dynamic image scenes without spatial registration of the hyperspectral data. This is advantageous compared to tunable filter based systems which need sophisticated image registration techniques. While tunable filters provide full spatial and spectral resolution, for CTIS systems there is always a tradeoff between spatial and spectral resolution as the spatial and spectral information corresponding to an image cube is squeezed onto a 2D image. The presented CTIS system uses a spectral-dispersion element to project the spectral and spatial image information onto a 2D CCD camera array. The system presented in this paper is designed for a microscopy application for the analysis of fixed specimens in pathology and cytogenetics, cell imaging and material analysis. However, the CTIS approach is not limited to microscopy applications, thus it would be possible to implement it in a hand-held device for e.g. real-time, intra-surgery tissue classification.

  2. Nonlinear spectral imaging of human normal skin, basal cell carcinoma and squamous cell carcinoma based on two-photon excited fluorescence and second-harmonic generation

    Science.gov (United States)

    Xiong, S. Y.; Yang, J. G.; Zhuang, J.

    2011-10-01

    In this work, we use nonlinear spectral imaging based on two-photon excited fluorescence (TPEF) and second harmonic generation (SHG) for analyzing the morphology of collagen and elastin and their biochemical variations in basal cell carcinoma (BCC), squamous cell carcinoma (SCC) and normal skin tissue. It was found in this work that there existed apparent differences among BCC, SCC and normal skin in terms of their thickness of the keratin and epithelial layers, their size of elastic fibers, as well as their distribution and spectral characteristics of collagen. These differences can potentially be used to distinguish BCC and SCC from normal skin, and to discriminate between BCC and SCC, as well as to evaluate treatment responses.

  3. Spectral theory and nonlinear functional analysis

    CERN Document Server

    Lopez-Gomez, Julian

    2001-01-01

    This Research Note addresses several pivotal problems in spectral theory and nonlinear functional analysis in connection with the analysis of the structure of the set of zeroes of a general class of nonlinear operators. It features the construction of an optimal algebraic/analytic invariant for calculating the Leray-Schauder degree, new methods for solving nonlinear equations in Banach spaces, and general properties of components of solutions sets presented with minimal use of topological tools. The author also gives several applications of the abstract theory to reaction diffusion equations and systems.The results presented cover a thirty-year period and include recent, unpublished findings of the author and his coworkers. Appealing to a broad audience, Spectral Theory and Nonlinear Functional Analysis contains many important contributions to linear algebra, linear and nonlinear functional analysis, and topology and opens the door for further advances.

  4. Matched Spectral Filter Imager Project

    Data.gov (United States)

    National Aeronautics and Space Administration — OPTRA proposes the development of an imaging spectrometer for greenhouse gas and volcanic gas imaging based on matched spectral filtering and compressive imaging....

  5. Power Spectral Density Conversions and Nonlinear Dynamics

    Directory of Open Access Journals (Sweden)

    Mostafa Rassaian

    1994-01-01

    Full Text Available To predict the vibration environment of a payload carried by a ground or air transporter, mathematical models are required from which a transfer function to a prescribed input can be calculated. For sensitive payloads these models typically include linear shock isolation system stiffness and damping elements relying on the assumption that the isolation system has a predetermined characteristic frequency and damping ratio independent of excitation magnitude. In order to achieve a practical spectral analysis method, the nonlinear system has to be linearized when the input transportation and handling vibration environment is in the form of an acceleration power spectral density. Test data from commercial isolators show that when nonlinear stiffness and damping effects exist the level of vibration input causes a variation in isolator resonant frequency. This phenomenon, described by the stationary response of the Duffing oscillator to narrow-band Gaussian random excitation, requires an alternative approach for calculation of power spectral density acceleration response at a shock isolated payload under random vibration. This article details the development of a plausible alternative approach for analyzing the spectral response of a nonlinear system subject to random Gaussian excitations.

  6. Wavelength conversion based spectral imaging

    DEFF Research Database (Denmark)

    Dam, Jeppe Seidelin

    There has been a strong, application driven development of Si-based cameras and spectrometers for imaging and spectral analysis of light in the visible and near infrared spectral range. This has resulted in very efficient devices, with high quantum efficiency, good signal to noise ratio and high...... resolution for this spectral region. Today, an increasing number of applications exists outside the spectral region covered by Si-based devices, e.g. within cleantech, medical or food imaging. We present a technology based on wavelength conversion which will extend the spectral coverage of state of the art...... visible or near infrared cameras and spectrometers to include other spectral regions of interest....

  7. Optimized spectral estimation for nonlinear synchronizing systems.

    Science.gov (United States)

    Sommerlade, Linda; Mader, Malenka; Mader, Wolfgang; Timmer, Jens; Thiel, Marco; Grebogi, Celso; Schelter, Björn

    2014-03-01

    In many fields of research nonlinear dynamical systems are investigated. When more than one process is measured, besides the distinct properties of the individual processes, their interactions are of interest. Often linear methods such as coherence are used for the analysis. The estimation of coherence can lead to false conclusions when applied without fulfilling several key assumptions. We introduce a data driven method to optimize the choice of the parameters for spectral estimation. Its applicability is demonstrated based on analytical calculations and exemplified in a simulation study. We complete our investigation with an application to nonlinear tremor signals in Parkinson's disease. In particular, we analyze electroencephalogram and electromyogram data.

  8. A spectral characterization of nonlinear normal modes

    Science.gov (United States)

    Cirillo, G. I.; Mauroy, A.; Renson, L.; Kerschen, G.; Sepulchre, R.

    2016-09-01

    This paper explores the relationship that exists between nonlinear normal modes (NNMs) defined as invariant manifolds in phase space and the spectral expansion of the Koopman operator. Specifically, we demonstrate that NNMs correspond to zero level sets of specific eigenfunctions of the Koopman operator. Thanks to this direct connection, a new, global parametrization of the invariant manifolds is established. Unlike the classical parametrization using a pair of state-space variables, this parametrization remains valid whenever the invariant manifold undergoes folding, which extends the computation of NNMs to regimes of greater energy. The proposed ideas are illustrated using a two-degree-of-freedom system with cubic nonlinearity.

  9. Nonlinear phased array imaging

    Science.gov (United States)

    Croxford, Anthony J.; Cheng, Jingwei; Potter, Jack N.

    2016-04-01

    A technique is presented for imaging acoustic nonlinearity within a specimen using ultrasonic phased arrays. Acoustic nonlinearity is measured by evaluating the difference in energy of the transmission bandwidth within the diffuse field produced through different focusing modes. The two different modes being classical beam forming, where delays are applied to different element of a phased array to physically focus the energy at a single location (parallel firing) and focusing in post processing, whereby one element at a time is fired and a focused image produced in post processing (sequential firing). Although these two approaches are linearly equivalent the difference in physical displacement within the specimen leads to differences in nonlinear effects. These differences are localized to the areas where the amplitude is different, essentially confining the differences to the focal point. Direct measurement at the focal point are however difficult to make. In order to measure this the diffuse field is used. It is a statistical property of the diffuse field that it represents the total energy in the system. If the energy in the diffuse field for both the sequential and parallel firing case is measured then the difference between these, within the input signal bandwidth, is largely due to differences at the focal spot. This difference therefore gives a localized measurement of where energy is moving out of the transmission bandwidth due to nonlinear effects. This technique is used to image fatigue cracks and other damage types undetectable with conventional linear ultrasonic measurements.

  10. Spectral decomposition of nonlinear systems with memory.

    Science.gov (United States)

    Svenkeson, Adam; Glaz, Bryan; Stanton, Samuel; West, Bruce J

    2016-02-01

    We present an alternative approach to the analysis of nonlinear systems with long-term memory that is based on the Koopman operator and a Lévy transformation in time. Memory effects are considered to be the result of interactions between a system and its surrounding environment. The analysis leads to the decomposition of a nonlinear system with memory into modes whose temporal behavior is anomalous and lacks a characteristic scale. On average, the time evolution of a mode follows a Mittag-Leffler function, and the system can be described using the fractional calculus. The general theory is demonstrated on the fractional linear harmonic oscillator and the fractional nonlinear logistic equation. When analyzing data from an ill-defined (black-box) system, the spectral decomposition in terms of Mittag-Leffler functions that we propose may uncover inherent memory effects through identification of a small set of dynamically relevant structures that would otherwise be obscured by conventional spectral methods. Consequently, the theoretical concepts we present may be useful for developing more general methods for numerical modeling that are able to determine whether observables of a dynamical system are better represented by memoryless operators, or operators with long-term memory in time, when model details are unknown.

  11. Electro-Optic Imaging Fourier Transform Spectral Polarimeter Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Boulder Nonlinear Systems, Inc. (BNS) proposes to develop an Electro-Optic Imaging Fourier Transform Spectral Polarimeter (E-O IFTSP). The polarimetric system is...

  12. Rapid spectral analysis for spectral imaging.

    Science.gov (United States)

    Jacques, Steven L; Samatham, Ravikant; Choudhury, Niloy

    2010-07-15

    Spectral imaging requires rapid analysis of spectra associated with each pixel. A rapid algorithm has been developed that uses iterative matrix inversions to solve for the absorption spectra of a tissue using a lookup table for photon pathlength based on numerical simulations. The algorithm uses tissue water content as an internal standard to specify the strength of optical scattering. An experimental example is presented on the spectroscopy of portwine stain lesions. When implemented in MATLAB, the method is ~100-fold faster than using fminsearch().

  13. Rayleigh imaging in spectral mammography

    Science.gov (United States)

    Berggren, Karl; Danielsson, Mats; Fredenberg, Erik

    2016-03-01

    Spectral imaging is the acquisition of multiple images of an object at different energy spectra. In mammography, dual-energy imaging (spectral imaging with two energy levels) has been investigated for several applications, in particular material decomposition, which allows for quantitative analysis of breast composition and quantitative contrast-enhanced imaging. Material decomposition with dual-energy imaging is based on the assumption that there are two dominant photon interaction effects that determine linear attenuation: the photoelectric effect and Compton scattering. This assumption limits the number of basis materials, i.e. the number of materials that are possible to differentiate between, to two. However, Rayleigh scattering may account for more than 10% of the linear attenuation in the mammography energy range. In this work, we show that a modified version of a scanning multi-slit spectral photon-counting mammography system is able to acquire three images at different spectra and can be used for triple-energy imaging. We further show that triple-energy imaging in combination with the efficient scatter rejection of the system enables measurement of Rayleigh scattering, which adds an additional energy dependency to the linear attenuation and enables material decomposition with three basis materials. Three available basis materials have the potential to improve virtually all applications of spectral imaging.

  14. Multi-spectral imager

    CSIR Research Space (South Africa)

    Stolper, R

    2006-02-01

    Full Text Available This poster highlights the design and development of a camera which combines ultraviolet, infrared and visual imaging techniques for advanced diagnostic inspections, and also shows some evaluations carried out to demonstrate the operability...

  15. Nonlinear Ultrasonic Phased Array Imaging

    Science.gov (United States)

    Potter, J. N.; Croxford, A. J.; Wilcox, P. D.

    2014-10-01

    This Letter reports a technique for the imaging of acoustic nonlinearity. By contrasting the energy of the diffuse field produced through the focusing of an ultrasonic array by delayed parallel element transmission with that produced by postprocessing of sequential transmission data, acoustic nonlinearity local to the focal point is measured. Spatially isolated wave distortion is inferred without requiring interrogation of the wave at the inspection point, thereby allowing nonlinear imaging through depth.

  16. Nonlinear ultrasonic phased array imaging

    OpenAIRE

    Potter, J N; Croxford, A.J.; Wilcox, P. D.

    2014-01-01

    This Letter reports a technique for the imaging of acoustic nonlinearity. By contrasting the energy of the diffuse field produced through the focusing of an ultrasonic array by delayed parallel element transmission with that produced by postprocessing of sequential transmission data, acoustic nonlinearity local to the focal point is measured. Spatially isolated wave distortion is inferred without requiring interrogation of the wave at the inspection point, thereby allowing nonlinear imaging t...

  17. Nonlinear ultrasonic phased array imaging.

    Science.gov (United States)

    Potter, J N; Croxford, A J; Wilcox, P D

    2014-10-03

    This Letter reports a technique for the imaging of acoustic nonlinearity. By contrasting the energy of the diffuse field produced through the focusing of an ultrasonic array by delayed parallel element transmission with that produced by postprocessing of sequential transmission data, acoustic nonlinearity local to the focal point is measured. Spatially isolated wave distortion is inferred without requiring interrogation of the wave at the inspection point, thereby allowing nonlinear imaging through depth.

  18. Fluorescence and Spectral Imaging

    Directory of Open Access Journals (Sweden)

    Ralph S. DaCosta

    2007-01-01

    Full Text Available Early identification of dysplasia remains a critical goal for diagnostic endoscopy since early discovery directly improves patient survival because it allows endoscopic or surgical intervention with disease localized without lymph node involvement. Clinical studies have successfully used tissue autofluorescence with conventional white light endoscopy and biopsy for detecting adenomatous colonic polyps, differentiating benign hyperplastic from adenomas with acceptable sensitivity and specificity. In Barrett's esophagus, the detection of dysplasia remains problematic because of background inflammation, whereas in the squamous esophagus, autofluorescence imaging appears to be more dependable. Point fluorescence spectroscopy, although playing a crucial role in the pioneering mechanistic development of fluorescence endoscopic imaging, does not seem to have a current function in endoscopy because of its nontargeted sampling and suboptimal sensitivity and specificity. Other point spectroscopic modalities, such as Raman spectroscopy and elastic light scattering, continue to be evaluated in clinical studies, but still suffer the significant disadvantages of being random and nonimaging. A recent addition to the fluorescence endoscopic imaging arsenal is the use of confocal fluorescence endomicroscopy, which provides real-time optical biopsy for the first time. To improve detection of dysplasia in the gastrointestinal tract, a new and exciting development has been the use of exogenous fluorescence contrast probes that specifically target a variety of disease-related cellular biomarkers using conventional fluorescent dyes and novel potent fluorescent nanocrystals (i.e., quantum dots. This is an area of great promise, but still in its infancy, and preclinical studies are currently under way.

  19. Resolution enhancement in nonlinear photoacoustic imaging

    Energy Technology Data Exchange (ETDEWEB)

    Goy, Alexandre S.; Fleischer, Jason W. [Department of Electrical Engineering, Princeton University, Olden St., Princeton, New Jersey 08544 (United States)

    2015-11-23

    Nonlinear processes can be exploited to gain access to more information than is possible in the linear regime. Nonlinearity modifies the spectra of the excitation signals through harmonic generation, frequency mixing, and spectral shifting, so that features originally outside the detector range can be detected. Here, we present an experimental study of resolution enhancement for photoacoustic imaging of thin metal layers immersed in water. In this case, there is a threshold in the excitation below which no acoustic signal is detected. Above threshold, the nonlinearity reduces the width of the active area of the excitation beam, resulting in a narrower absorption region and thus improved spatial resolution. This gain is limited only by noise, as the active area of the excitation can be arbitrarily reduced when the fluence becomes closer to the threshold. Here, we demonstrate a two-fold improvement in resolution and quantify the image quality as the excitation fluence goes through threshold.

  20. Spectral theory and nonlinear analysis with applications to spatial ecology

    CERN Document Server

    Cano-Casanova, S; Mora-Corral , C

    2005-01-01

    This volume details some of the latest advances in spectral theory and nonlinear analysis through various cutting-edge theories on algebraic multiplicities, global bifurcation theory, non-linear Schrödinger equations, non-linear boundary value problems, large solutions, metasolutions, dynamical systems, and applications to spatial ecology. The main scope of the book is bringing together a series of topics that have evolved separately during the last decades around the common denominator of spectral theory and nonlinear analysis - from the most abstract developments up to the most concrete applications to population dynamics and socio-biology - in an effort to fill the existing gaps between these fields.

  1. Coherent fiber supercontinuum laser for nonlinear biomedical imaging

    Science.gov (United States)

    Tu, Haohua; Liu, Yuan; Liu, Xiaomin; Lægsgaard, Jesper; Turchinovich, Dmitry; Boppart, Stephen A.

    2012-12-01

    Nonlinear biomedical imaging has not benefited from the well-known techniques of fiber supercontinuum generation for reasons such as poor coherence (or high noise), insufficient controllability, low spectral power intensity, and inadequate portability. Fortunately, a few techniques involving nonlinear fiber optics and femtosecond fiber laser development have emerged to overcome these critical limitations. These techniques pave the way for conducting point-of-care nonlinear biomedical imaging by a low-maintenance cost-effective coherent fiber supercontinuum laser, which covers a broad emission wavelength of 350-1700 nm. A prototype of this laser has been demonstrated in label-free multimodal nonlinear imaging of cell and tissue samples.

  2. Nonlinear Spectral-Spatial Control and Localization of Supercontinuum Radiation

    Science.gov (United States)

    Neshev, Dragomir N.; Sukhorukov, Andrey A.; Dreischuh, Alexander; Fischer, Robert; Ha, Sangwoo; Bolger, Jeremy; Bui, Lam; Krolikowski, Wieslaw; Eggleton, Benjamin J.; Mitchell, Arnan; Austin, Michael W.; Kivshar, Yuri S.

    2007-09-01

    We present the first observation of spatiospectral control and localization of supercontinuum light through the nonlinear interaction of spectral components in extended periodic structures. We use an array of optical waveguides in a LiNbO3 crystal and employ the interplay between diffraction and nonlinearity to dynamically control the output spectrum of the supercontinuum radiation. This effect presents an efficient scheme for optically tunable spectral filtering of supercontinua.

  3. Nonlinear physical systems spectral analysis, stability and bifurcations

    CERN Document Server

    Kirillov, Oleg N

    2013-01-01

    Bringing together 18 chapters written by leading experts in dynamical systems, operator theory, partial differential equations, and solid and fluid mechanics, this book presents state-of-the-art approaches to a wide spectrum of new and challenging stability problems.Nonlinear Physical Systems: Spectral Analysis, Stability and Bifurcations focuses on problems of spectral analysis, stability and bifurcations arising in the nonlinear partial differential equations of modern physics. Bifurcations and stability of solitary waves, geometrical optics stability analysis in hydro- and magnetohydrodynam

  4. Online Fault Diagnosis Method Based on Nonlinear Spectral Analysis

    Institute of Scientific and Technical Information of China (English)

    WEI Rui-xuan; WU Li-xun; WANG Yong-chang; HAN Chong-zhao

    2005-01-01

    The fault diagnosis based on nonlinear spectral analysis is a new technique for the nonlinear fault diagnosis, but its online application could be limited because of the enormous compution requirements for the estimation of general frequency response functions. Based on the fully decoupled Volterra identification algorithm, a new online fault diagnosis method based on nonlinear spectral analysis is presented, which can availably reduce the online compution requirements of general frequency response functions. The composition and working principle of the method are described, the test experiments have been done for damping spring of a vehicle suspension system by utilizing the new method, and the results indicate that the method is efficient.

  5. Active spectral imaging and mapping

    Science.gov (United States)

    Steinvall, Ove

    2014-04-01

    Active imaging and mapping using lasers as illumination sources have been of increasing interest during the last decades. Applications range from defense and security, remote sensing, medicine, robotics, and others. So far, these laser systems have mostly been based on a fix wavelength laser. Recent advances in lasers enable emission of tunable, multiline, or broadband emission, which together with the development of array detectors will extend the capabilities of active imaging and mapping. This paper will review some of the recent work on active imaging mainly for defense and security and remote sensing applications. A short survey of basic lidar relations and present fix wavelength laser systems is followed by a review of the benefits of adding the spectral dimension to active and/or passive electro-optical systems.

  6. Spectral clustering for TRUS images

    Directory of Open Access Journals (Sweden)

    Salama Magdy MA

    2007-03-01

    Full Text Available Abstract Background Identifying the location and the volume of the prostate is important for ultrasound-guided prostate brachytherapy. Prostate volume is also important for prostate cancer diagnosis. Manual outlining of the prostate border is able to determine the prostate volume accurately, however, it is time consuming and tedious. Therefore, a number of investigations have been devoted to designing algorithms that are suitable for segmenting the prostate boundary in ultrasound images. The most popular method is the deformable model (snakes, a method that involves designing an energy function and then optimizing this function. The snakes algorithm usually requires either an initial contour or some points on the prostate boundary to be estimated close enough to the original boundary which is considered a drawback to this powerful method. Methods The proposed spectral clustering segmentation algorithm is built on a totally different foundation that doesn't involve any function design or optimization. It also doesn't need any contour or any points on the boundary to be estimated. The proposed algorithm depends mainly on graph theory techniques. Results Spectral clustering is used in this paper for both prostate gland segmentation from the background and internal gland segmentation. The obtained segmented images were compared to the expert radiologist segmented images. The proposed algorithm obtained excellent gland segmentation results with 93% average overlap areas. It is also able to internally segment the gland where the segmentation showed consistency with the cancerous regions identified by the expert radiologist. Conclusion The proposed spectral clustering segmentation algorithm obtained fast excellent estimates that can give rough prostate volume and location as well as internal gland segmentation without any user interaction.

  7. Nonlinearity detection in hyperspectral images using a polynomial post-nonlinear mixing model.

    Science.gov (United States)

    Altmann, Yoann; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2013-04-01

    This paper studies a nonlinear mixing model for hyperspectral image unmixing and nonlinearity detection. The proposed model assumes that the pixel reflectances are nonlinear functions of pure spectral components contaminated by an additive white Gaussian noise. These nonlinear functions are approximated by polynomials leading to a polynomial post-nonlinear mixing model. We have shown in a previous paper that the parameters involved in the resulting model can be estimated using least squares methods. A generalized likelihood ratio test based on the estimator of the nonlinearity parameter is proposed to decide whether a pixel of the image results from the commonly used linear mixing model or from a more general nonlinear mixing model. To compute the test statistic associated with the nonlinearity detection, we propose to approximate the variance of the estimated nonlinearity parameter by its constrained Cramér-Rao bound. The performance of the detection strategy is evaluated via simulations conducted on synthetic and real data. More precisely, synthetic data have been generated according to the standard linear mixing model and three nonlinear models from the literature. The real data investigated in this study are extracted from the Cuprite image, which shows that some minerals seem to be nonlinearly mixed in this image. Finally, it is interesting to note that the estimated abundance maps obtained with the post-nonlinear mixing model are in good agreement with results obtained in previous studies.

  8. Spectral characteristics and nonlinear studies of crystal violet dye

    Science.gov (United States)

    Sukumaran, V. Sindhu; Ramalingam, A.

    2006-03-01

    Solid-state dye-doped polymer is an attractive alternative to the conventional liquid dye solution. In this paper, the spectral characteristics and the nonlinear optical properties of the dye crystal violet are studied. The spectral characteristics of crystal violet dye doped poly(methylmethacrylate) modified with additive n-butyl acetate (nBA) are studied by recording its absorption and fluorescence spectra and the results are compared with the corresponding liquid mixture. The nonlinear refractive index of the dye in nBA and dye doped polymer film were measured using z-scan technique, by exciting with He-Ne laser. The results obtained are intercompared. Both the samples of dye crystal violet show a negative nonlinear refractive index. The origin of optical nonlinearity in the dye may be attributed due to laser-heating induced nonlinear effect.

  9. Nonlinear intravascular ultrasound contrast imaging

    NARCIS (Netherlands)

    Goertz, David E.; Frijlink, Martijn E.; de Jong, N.; van der Steen, Antonius F.W.

    2006-01-01

    Nonlinear contrast agent imaging with intravascular ultrasound (IVUS) is investigated using a prototype IVUS system and an experimental small bubble contrast agent. The IVUS system employed a mechanically scanned single element transducer and was operated at a 20 MHz transmit frequency (F20) for

  10. Covariation of spectral and nonlinear EEG measures with alpha biofeedback.

    NARCIS (Netherlands)

    Fell, J.; Elfadil, H.; Klaver, P.; Roschke, J.; Elger, C.E.; Fernandez, G.S.E.

    2002-01-01

    This study investigated how different spectral and nonlinear EEG measures covaried with alpha power during auditory alpha biofeedback training, performed by 13 healthy subjects. We found a significant positive correlation of alpha power with the largest Lyapunov-exponent, pointing to an increased

  11. Spectral characteristics of Compton backscattering sources. Linear and nonlinear modes

    Energy Technology Data Exchange (ETDEWEB)

    Potylitsyn, A.P., E-mail: potylitsyn@tpu.ru [National Research Tomsk Polytechnic University, 634050 Tomsk (Russian Federation); National Research Nuclear University MEPhI, 115409 Moscow (Russian Federation); Kolchuzhkin, A.M. [Moscow State University of Technology “STANKIN”, 127994 Moscow (Russian Federation)

    2015-07-15

    Compton backscattering (CBS) of laser photons by relativistic electrons is widely used to design X-ray and gamma sources with a bandwidth better than 1% using a tight collimation. In order to obtain a reasonable intensity of the resulting beam one has to increase power of a laser pulse simultaneously with narrowing of the waist in the interaction point. It can lead to nonlinearity of CBS process which is affected on spectral characteristics of the collimated gamma beam (so-called “red-shift” of the spectral line, emission of “soft” photons with energy much less than the spectral line energy). In this paper we have analyzed such an influence using Monte-Carlo technique and have shown that even weak nonlinearity should be taken into account if the gamma beam is formed by a narrow aperture.

  12. Nonlinear infrared spectroscopy free from spectral selection

    Science.gov (United States)

    Paterova, Anna; Lung, Shaun; Kalashnikov, Dmitry A.; Krivitsky, Leonid A.

    2017-02-01

    Infrared (IR) spectroscopy is an indispensable tool for many practical applications including material analysis and sensing. Existing IR spectroscopy techniques face challenges related to the inferior performance and the high cost of IR-grade components. Here, we develop a new method, which allows studying properties of materials in the IR range using only visible light optics and detectors. It is based on the nonlinear interference of entangled photons, generated via Spontaneous Parametric Down Conversion (SPDC). In our interferometer, the phase of the signal photon in the visible range depends on the phase of an entangled IR photon. When the IR photon is traveling through the media, its properties can be found from observations of the visible photon. We directly acquire the SPDC signal with a visible range CCD camera and use a numerical algorithm to infer the absorption coefficient and the refraction index of the sample in the IR range. Our method does not require the use of a spectrometer and a slit, thus it allows achieving higher signal-to-noise ratio than the earlier developed method.

  13. Spectral lineshapes in nonlinear electronic spectroscopy.

    Science.gov (United States)

    Nenov, Artur; Giussani, Angelo; Fingerhut, Benjamin P; Rivalta, Ivan; Dumont, Elise; Mukamel, Shaul; Garavelli, Marco

    2015-12-14

    We outline a computational approach for nonlinear electronic spectra, which accounts for the electronic energy fluctuations due to nuclear degrees of freedom and explicitly incorporates the fluctuations of higher excited states, induced by the dynamics in the photoactive state(s). This approach is based on mixed quantum-classical dynamics simulations. Tedious averaging over multiple trajectories is avoided by employing the linearly displaced Brownian harmonic oscillator to model the correlation functions. The present strategy couples accurate computations of the high-lying excited state manifold with dynamics simulations. The application is made to the two-dimensional electronic spectra of pyrene, a polycyclic aromatic hydrocarbon characterized by an ultrafast (few tens of femtoseconds) decay from the bright S2 state to the dark S1 state. The spectra for waiting times t2 = 0 and t2 = 1 ps demonstrate the ability of this approach to model electronic state fluctuations and realistic lineshapes. Comparison with experimental spectra [Krebs et al., New Journal of Physics, 2013, 15, 085016] shows excellent agreement and allows us to unambiguously assign the excited state absorption features.

  14. Nonlinear infrared spectroscopy free from spectral selection

    CERN Document Server

    Paterova, Anna; Kalashnikov, Dmitry; Krivitsky, Leonid

    2016-01-01

    Infrared (IR) spectroscopy is an indispensable tool for many practical applications including material analysis and sensing. Existing IR spectroscopy techniques face challenges related to the inferior performance and the high cost of IR-grade components. Here, we develop a new method, which allows studying properties of materials in the IR range using only visible light optics and detectors. It is based on the nonlinear interference of entangled photons, generated via Spontaneous Parametric Down Conversion (SPDC). In our interferometer, the phase of the signal photon in the visible range depends on the phase of an entangled IR photon. When the IR photon is traveling through the media, its properties can be found from observations of the visible photon. We directly acquire the SPDC signal with a visible range CCD camera and use a numerical algorithm to infer the absorption coefficient and the refraction index of the sample in the IR range. Our method does not require the use of a spectrometer and a slit, thus ...

  15. Active spectral imaging nondestructive evaluation (SINDE) camera

    Energy Technology Data Exchange (ETDEWEB)

    Simova, E.; Rochefort, P.A., E-mail: eli.simova@cnl.ca [Canadian Nuclear Laboratories, Chalk River, Ontario (Canada)

    2016-06-15

    A proof-of-concept video camera for active spectral imaging nondestructive evaluation has been demonstrated. An active multispectral imaging technique has been implemented in the visible and near infrared by using light emitting diodes with wavelengths spanning from 400 to 970 nm. This shows how the camera can be used in nondestructive evaluation to inspect surfaces and spectrally identify materials and corrosion. (author)

  16. Urban Impervious Surface Extraction from Remote Sensing Image Based on Nonlinear Spectral Mixture Model%基于非线性光谱混合模型的遥感影像提取城市不透水层

    Institute of Scientific and Technical Information of China (English)

    夏俊士; 杜培军; 曹文

    2011-01-01

    Aiming at overcoming the limitations in extracting impervious surface by traditional methods, two non-linear spectral mixture models, Mixture Tuned Matched Filtering (MTMF)and Multi-Layer Perceptron(MLP) neural network, are used to decompose all pixels to the four fraction images representing the abundance of four endmembers. In these models, MTMF performs a "partial" unmixing by only finding the abundance of a single, user-defined endmember, by maximizing the response of the endmember of interest and minimizing the response of the composite unknown background. The MLP is a hierarchical structure of several perceptrons, and capable of learning a rich variety of nonlinear decision surfaces. The Maximum Noise Fraction(MNF) is used to transform the six bands of TM image into a new feature space and the first three components accounting for the majority (more than 90%) of total information content are used to endmember extraction. After that, the Pure Pixel Index(PPI) is used to select pure pixels. The N-dimensional visualizer is used for assisting selection of four endmembers: vegetation, high-albedo objects, low-albedo objects and soil. The fraction images are derived to represent the abundance of the above four endmember. Impervious surface is estimated by analyzing high-albedo and low-albedo fraction images. QuickBird multi-spectral image is used to evaluate the accuracy of impervious surface extraction by different methods.Experimental results indicate that the accuracy of artificial neural network is higher than others,which means non-linear spectral mixture models is also effective to impervious area extraction,even better than linear models.%针对传统方法在提取城市不透水层中的许多局限性,采用两种非线性光谱混合分解模型,包括混合调谐匹配滤波和多层感知器神经网络,通过混合像元分解获取城市不透水层.混合调谐匹配滤波利用用户选择的端元,通过最大化端元响应并减少未知背

  17. Non-linear Ultrasound Imaging

    DEFF Research Database (Denmark)

    Du, Yigang

    without iteration steps. The ASA is implemented in combination with Field II and extended to simulate the pulsed ultrasound fields. The simulated results from a linear array transducer are made by the ASA based on Field II, and by a released non-linear simulation program- Abersim, respectively....... The calculation speed of the ASA is increased approximately by a factor of 140. For the second harmonic point spread function the error of the full width is 1.5% at -6 dB and 6.4% at -12 dB compared to Abersim. To further investigate the linear and non-linear ultrasound fields, hydrophone measurements.......3% relative to the measurement from a 1 inch diameter transducer. A preliminary study for harmonic imaging using synthetic aperture sequential beamforming (SASB) has been demonstrated. A wire phantom underwater measurement is made by an experimental synthetic aperture real-time ultrasound scanner (SARUS...

  18. Spectral and nonlinear studies of night blue dye

    Science.gov (United States)

    Sindhu Sukumaran, V.; Ramalingam, A.

    2006-12-01

    Solid-state dye-doped polymer is an attractive alternative to the conventional liquid dye solution. In this Letter the spectral characteristics and the nonlinear optical properties of the dye night blue are studied. The spectral characteristics of night blue dye doped poly(methylmethacrylate) modified with additive n-butyl acetate (nBA) are studied by recording its absorption and fluorescence spectra and the results are compared with the corresponding liquid mixture. The nonlinear refractive index of the dye in nBA and dye doped polymer film were measured using z-scan technique [S.-B., Mansoor, A.A. Said, T.-H. Wei, D.J. Hagan, E.W. Van Stryland, IEEE J. Quantum Electron. 26 (1990) 760], by exciting with He Ne laser. The results obtained are intercompared. Both the samples of dye night blue show a negative nonlinear refractive index. The origin of optical nonlinearity in the dye may be attributed due to laser-heating induced nonlinear effect.

  19. Coherent fiber supercontinuum laser for nonlinear biomedical imaging

    DEFF Research Database (Denmark)

    Tu, Haohua; Liu, Yuan; Liu, Xiaomin;

    2012-01-01

    Nonlinear biomedical imaging has not benefited from the well-known techniques of fiber supercontinuum generation for reasons such as poor coherence (or high noise), insufficient controllability, low spectral power intensity, and inadequate portability. Fortunately, a few techniques involving...... nonlinear fiber optics and femtosecond fiber laser development have emerged to overcome these critical limitations. These techniques pave the way for conducting point-of-care nonlinear biomedical imaging by a low-maintenance cost-effective coherent fiber supercontinuum laser, which covers a broad emission...... wavelength of 350-1700 nm. A prototype of this laser has been demonstrated in label-free multimodal nonlinear imaging of cell and tissue samples.© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only....

  20. Spectral Imaging at the Microscale and Beyond

    Directory of Open Access Journals (Sweden)

    François Paquet-Mercier

    2014-05-01

    Full Text Available Here we give context to the special issue “Spectral Imaging at the Microscale and Beyond” in Sensors. We start with an introduction and motivation for the need for spectral imaging and then present important definitions and background concepts. Following this, we review new developments and applications in environmental monitoring, biomaterials, microfluidics, nanomaterials, healthcare, agriculture and food science, with a special focus on the articles published in the special issue. Some concluding remarks put the presented developments in context vis-à-vis the future of spectral imaging.

  1. Quantitative spectrally resolved imaging through a spectrograph

    NARCIS (Netherlands)

    Tolboom, RAL; Sijtsema, NM; ter Meulen, JJ; Dam, N.J.

    2003-01-01

    A grating spectrograph can be used for spectrally selective two-dimensional imaging if it is operated with a broad entrance slit. The resulting intensity distribution in its exit plane is a one-dimensional convolution of the spatial and spectral distributions of incident light. We present a dedicate

  2. Spectral Reconstruction for Obtaining Virtual Hyperspectral Images

    Science.gov (United States)

    Perez, G. J. P.; Castro, E. C.

    2016-12-01

    Hyperspectral sensors demonstrated its capabalities in identifying materials and detecting processes in a satellite scene. However, availability of hyperspectral images are limited due to the high development cost of these sensors. Currently, most of the readily available data are from multi-spectral instruments. Spectral reconstruction is an alternative method to address the need for hyperspectral information. The spectral reconstruction technique has been shown to provide a quick and accurate detection of defects in an integrated circuit, recovers damaged parts of frescoes, and it also aids in converting a microscope into an imaging spectrometer. By using several spectral bands together with a spectral library, a spectrum acquired by a sensor can be expressed as a linear superposition of elementary signals. In this study, spectral reconstruction is used to estimate the spectra of different surfaces imaged by Landsat 8. Four atmospherically corrected surface reflectance from three visible bands (499 nm, 585 nm, 670 nm) and one near-infrared band (872 nm) of Landsat 8, and a spectral library of ground elements acquired from the United States Geological Survey (USGS) are used. The spectral library is limited to 420-1020 nm spectral range, and is interpolated at one nanometer resolution. Singular Value Decomposition (SVD) is used to calculate the basis spectra, which are then applied to reconstruct the spectrum. The spectral reconstruction is applied for test cases within the library consisting of vegetation communities. This technique was successful in reconstructing a hyperspectral signal with error of less than 12% for most of the test cases. Hence, this study demonstrated the potential of simulating information at any desired wavelength, creating a virtual hyperspectral sensor without the need for additional satellite bands.

  3. Spectral calibration for convex grating imaging spectrometer

    Science.gov (United States)

    Zhou, Jiankang; Chen, Xinhua; Ji, Yiqun; Chen, Yuheng; Shen, Weimin

    2013-12-01

    Spectral calibration of imaging spectrometer plays an important role for acquiring target accurate spectrum. There are two spectral calibration types in essence, the wavelength scanning and characteristic line sampling. Only the calibrated pixel is used for the wavelength scanning methods and he spectral response function (SRF) is constructed by the calibrated pixel itself. The different wavelength can be generated by the monochromator. The SRF is constructed by adjacent pixels of the calibrated one for the characteristic line sampling methods. And the pixels are illuminated by the narrow spectrum line and the center wavelength of the spectral line is exactly known. The calibration result comes from scanning method is precise, but it takes much time and data to deal with. The wavelength scanning method cannot be used in field or space environment. The characteristic line sampling method is simple, but the calibration precision is not easy to confirm. The standard spectroscopic lamp is used to calibrate our manufactured convex grating imaging spectrometer which has Offner concentric structure and can supply high resolution and uniform spectral signal. Gaussian fitting algorithm is used to determine the center position and the Full-Width-Half-Maximum(FWHM)of the characteristic spectrum line. The central wavelengths and FWHMs of spectral pixels are calibrated by cubic polynomial fitting. By setting a fitting error thresh hold and abandoning the maximum deviation point, an optimization calculation is achieved. The integrated calibration experiment equipment for spectral calibration is developed to enhance calibration efficiency. The spectral calibration result comes from spectral lamp method are verified by monochromator wavelength scanning calibration technique. The result shows that spectral calibration uncertainty of FWHM and center wavelength are both less than 0.08nm, or 5.2% of spectral FWHM.

  4. Spectral image analysis of mutual illumination between florescent objects.

    Science.gov (United States)

    Tominaga, Shoji; Kato, Keiji; Hirai, Keita; Horiuchi, Takahiko

    2016-08-01

    This paper proposes a method for modeling and component estimation of the spectral images of the mutual illumination phenomenon between two fluorescent objects. First, we briefly describe the bispectral characteristics of a single fluorescent object, which are summarized as a Donaldson matrix. We suppose that two fluorescent objects with different bispectral characteristics are located close together under a uniform illumination. Second, we model the mutual illumination between two objects. It is shown that the spectral composition of the mutual illumination is summarized with four components: (1) diffuse reflection, (2) diffuse-diffuse interreflection, (3) fluorescent self-luminescence, and (4) interreflection by mutual fluorescent illumination. Third, we develop algorithms for estimating the spectral image components from the observed images influenced by the mutual illumination. When the exact Donaldson matrices caused by the mutual illumination influence are unknown, we have to solve a non-linear estimation problem to estimate both the spectral functions and the location weights. An iterative algorithm is then proposed to solve the problem based on the alternate estimation of the spectral functions and the location weights. In our experiments, the feasibility of the proposed method is shown in three cases: the known Donaldson matrices, weak interreflection, and strong interreflection.

  5. Nonlinear susceptibility magnitude imaging of magnetic nanoparticles

    Energy Technology Data Exchange (ETDEWEB)

    Ficko, Bradley W., E-mail: Bradley.W.Ficko@Dartmouth.edu; Giacometti, Paolo; Diamond, Solomon G.

    2015-03-15

    This study demonstrates a method for improving the resolution of susceptibility magnitude imaging (SMI) using spatial information that arises from the nonlinear magnetization characteristics of magnetic nanoparticles (mNPs). In this proof-of-concept study of nonlinear SMI, a pair of drive coils and several permanent magnets generate applied magnetic fields and a coil is used as a magnetic field sensor. Sinusoidal alternating current (AC) in the drive coils results in linear mNP magnetization responses at primary frequencies, and nonlinear responses at harmonic frequencies and intermodulation frequencies. The spatial information content of the nonlinear responses is evaluated by reconstructing tomographic images with sequentially increasing voxel counts using the combined linear and nonlinear data. Using the linear data alone it is not possible to accurately reconstruct more than 2 voxels with a pair of drive coils and a single sensor. However, nonlinear SMI is found to accurately reconstruct 12 voxels (R{sup 2}=0.99, CNR=84.9) using the same physical configuration. Several time-multiplexing methods are then explored to determine if additional spatial information can be obtained by varying the amplitude, phase and frequency of the applied magnetic fields from the two drive coils. Asynchronous phase modulation, amplitude modulation, intermodulation phase modulation, and frequency modulation all resulted in accurate reconstruction of 6 voxels (R{sup 2}>0.9) indicating that time multiplexing is a valid approach to further increase the resolution of nonlinear SMI. The spatial information content of nonlinear mNP responses and the potential for resolution enhancement with time multiplexing demonstrate the concept and advantages of nonlinear SMI. - Highlights: • Development of a nonlinear susceptibility magnitude imaging model • Demonstration of nonlinear SMI with primary and harmonic frequencies • Demonstration of nonlinear SMI with primary and intermodulation

  6. CONSTRAINED SPECTRAL CLUSTERING FOR IMAGE SEGMENTATION

    OpenAIRE

    Sourati, Jamshid; Brooks, Dana H.; Dy, Jennifer G.; Erdogmus, Deniz

    2012-01-01

    Constrained spectral clustering with affinity propagation in its original form is not practical for large scale problems like image segmentation. In this paper we employ novelty selection sub-sampling strategy, besides using efficient numerical eigen-decomposition methods to make this algorithm work efficiently for images. In addition, entropy-based active learning is also employed to select the queries posed to the user more wisely in an interactive image segmentation framework. We evaluate ...

  7. Methodology for diagnosing of skin cancer on images of dermatologic spots by spectral analysis.

    Science.gov (United States)

    Guerra-Rosas, Esperanza; Álvarez-Borrego, Josué

    2015-10-01

    In this paper a new methodology for the diagnosing of skin cancer on images of dermatologic spots using image processing is presented. Currently skin cancer is one of the most frequent diseases in humans. This methodology is based on Fourier spectral analysis by using filters such as the classic, inverse and k-law nonlinear. The sample images were obtained by a medical specialist and a new spectral technique is developed to obtain a quantitative measurement of the complex pattern found in cancerous skin spots. Finally a spectral index is calculated to obtain a range of spectral indices defined for skin cancer. Our results show a confidence level of 95.4%.

  8. Multi Spectral Fluorescence Imager (MSFI)

    Science.gov (United States)

    Caron, Allison

    2016-01-01

    Genetic transformation with in vivo reporter genes for fluorescent proteins can be performed on a variety of organisms to address fundamental biological questions. Model organisms that may utilize an ISS imager include unicellular organisms (Saccharomyces cerevisiae), plants (Arabidopsis thaliana), and invertebrates (Caenorhabditis elegans). The multispectral fluorescence imager (MSFI) will have the capability to accommodate 10 cm x 10 cm Petri plates, various sized multi-well culture plates, and other custom culture containers. Features will include programmable temperature and light cycles, ethylene scrubbing (less than 25 ppb), CO2 control (between 400 ppm and ISS-ambient levels in units of 100 ppm) and sufficient airflow to prevent condensation that would interfere with imaging.

  9. Video rate spectral imaging using a coded aperture snapshot spectral imager.

    Science.gov (United States)

    Wagadarikar, Ashwin A; Pitsianis, Nikos P; Sun, Xiaobai; Brady, David J

    2009-04-13

    We have previously reported on coded aperture snapshot spectral imagers (CASSI) that can capture a full frame spectral image in a snapshot. Here we describe the use of CASSI for spectral imaging of a dynamic scene at video rate. We describe significant advances in the design of the optical system, system calibration procedures and reconstruction method. The new optical system uses a double Amici prism to achieve an in-line, direct view configuration, resulting in a substantial improvement in image quality. We describe NeAREst, an algorithm for estimating the instantaneous three-dimensional spatio-spectral data cube from CASSI's two-dimensional array of encoded and compressed measurements. We utilize CASSI's snapshot ability to demonstrate a spectral image video of multi-colored candles with live flames captured at 30 frames per second.

  10. Image Enhancement by Spectral Ratioing,

    Science.gov (United States)

    1980-06-01

    images et Vacquisition d’objectif dans 1’ infrarouge ", DREV R-4050/76, avril 1976, NON CIASSIFIE. UNCLASSIFIED 16 7. Sdvigny, L., "Simulation d’un syst...me d’acquisition automatique d’objectif infrarouge dans un contexte sol-sol", DREV R-4081/77, juin 1977, NON CIASSIFIE. 8. S6vigny, L., "La...reconnaissance de forme et I’acquisition d’objectif en infrarouge : Nouvel algorithme de detection", DREV R-4099/78, mars 1979, NON CEASSIFIE. 9. Panda, D.P

  11. Spectrally Consistent Satellite Image Fusion with Improved Image Priors

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg; Aanæs, Henrik; Jensen, Thomas B.S.;

    2006-01-01

    Here an improvement to our previous framework for satellite image fusion is presented. A framework purely based on the sensor physics and on prior assumptions on the fused image. The contributions of this paper are two fold. Firstly, a method for ensuring 100% spectrally consistency is proposed......, even when more sophisticated image priors are applied. Secondly, a better image prior is introduced, via data-dependent image smoothing....

  12. A Hierarchy of New Nonlinear Evolution Equations Associated with a 3 × 3 Matrix Spectral Problem

    Institute of Scientific and Technical Information of China (English)

    GENG Xian-Guo; LI Fang

    2009-01-01

    A 3 × 3 matrix spectral problem with three potentials and the corresponding hierarchy of new nonlinear evolution equations are proposed. Generalized Hamiltonian structures for the hierarchy of nonlinear evolution equations are derived with the aid of trace identity.

  13. Compressive sensing with dispersion compensation on non-linear wavenumber sampled spectral domain optical coherence tomography.

    Science.gov (United States)

    Xu, Daguang; Huang, Yong; Kang, Jin U

    2013-01-01

    We propose a novel compressive sensing (CS) method on spectral domain optical coherence tomography (SDOCT). By replacing the widely used uniform discrete Fourier transform (UDFT) matrix with a new sensing matrix which is a modification of the non-uniform discrete Fourier transform (NUDFT) matrix, it is shown that undersampled non-linear wavenumber spectral data can be used directly in the CS reconstruction. Thus k-space grid filling and k-linear mask calibration which were proposed to obtain linear wavenumber sampling from the non-linear wavenumber interferometric spectra in previous studies of CS in SDOCT (CS-SDOCT) are no longer needed. The NUDFT matrix is modified to promote the sparsity of reconstructed A-scans by making them symmetric while preserving the value of the desired half. In addition, we show that dispersion compensation can be implemented by multiplying the frequency-dependent correcting phase directly to the real spectra, eliminating the need for constructing complex component of the real spectra. This enables the incorporation of dispersion compensation into the CS reconstruction by adding the correcting term to the modified NUDFT matrix. With this new sensing matrix, A-scan with dispersion compensation can be reconstructed from undersampled non-linear wavenumber spectral data by CS reconstruction. Experimental results show that proposed method can achieve high quality imaging with dispersion compensation.

  14. Miniaturized spectral imager for Aalto-1 nanosatellite

    Science.gov (United States)

    Mannila, Rami; Näsilä, Antti; Praks, Jaan; Saari, Heikki; Antila, Jarkko

    2011-11-01

    The Aalto-1 is a 3U-cubesat project coordinated by Aalto University. The satellite, Aalto-1, will be mainly built by students as project assignments and thesis works. VTT Technical Research Centre of Finland will develop the main Earth observation payload, a miniaturized spectral imager, for the satellite. It is a novel highly miniaturized tunable filter type spectral imager. Mass of the spectral imager will be less than 400 grams, and dimensions will be approximately 80 mm x 80 mm x 45 mm. The spectral imager is based on a tunable Fabry-Pérot interferometer (FPI) accompanied by an RGB CMOS image sensor. The FPI consists of two highly reflective surfaces separated by a tunable air gap and it is based either on a microelectromechanical (MEMS) or piezo-actuated structure. The MEMS FPI is a monolithic device, i.e. it is made entirely on one substrate in a batch process, without assembling separate pieces together. The gap is adjusted by moving the upper mirror with electrostatic force. Benefits of the MEMS FPI are low mass and small size. However, large aperture (2-10 mm) MEMS FPIs are currently under development, thus it is not yet known if their performance is adequate. The piezo-actuated FPI uses three piezo-actuators and is controlled in a closed capacitive feedback loop. The drawback of the piezo-actuated FPI is its higher mass. However, it has a large aperture which enables a shorter exposure times. Selection of the FPI type will be done after thorough evaluation. Depending on the selected FPI type, the spectral resolution of the imager will be 5 - 10 nm at full width at half maximum and it will operate in the visible and/or near infrared range.

  15. Precise Multi-Spectral Dermatological Imaging

    DEFF Research Database (Denmark)

    Gomez, David Delgado; Carstensen, Jens Michael; Ersbøll, Bjarne Kjær

    2004-01-01

    . These spectral bands vary from ultraviolet to near infrared. The welldefined and diffuse illumination of the optically closed scene aims to avoid shadows and specular reflections. Furthermore, the system has been developed to guarantee the reproducibility of the collected images. This allows for comparative...

  16. Multiple snapshot colored compressive spectral imager

    Science.gov (United States)

    Correa, Claudia V.; Hinojosa, Carlos A.; Arce, Gonzalo R.; Arguello, Henry

    2017-04-01

    The snapshot colored compressive spectral imager (SCCSI) is a recent compressive spectral imaging (CSI) architecture that senses the spatial and spectral information of a scene in a single snapshot by means of a colored mosaic FPA detector and a dispersive element. Commonly, CSI architectures allow multiple snapshot acquisition, yielding improved reconstructions of spatially detailed and spectrally rich scenes. Each snapshot is captured employing a different coding pattern. In principle, SCCSI does not admit multiple snapshots since the pixelated tiling of optical filters is directly attached to the detector. This paper extends the concept of SCCSI to a system admitting multiple snapshot acquisition by rotating the dispersive element, so the dispersed spatio-spectral source is coded and integrated at different detector pixels in each rotation. Thus, a different set of coded projections is captured using the same optical components of the original architecture. The mathematical model of the multishot SCCSI system is presented along with several simulations. Results show that a gain up to 7 dB of peak signal-to-noise ratio is achieved when four SCCSI snapshots are compared to a single snapshot reconstruction. Furthermore, a gain up to 5 dB is obtained with respect to state-of-the-art architecture, the multishot CASSI.

  17. Study of image motion compensation in spectral imaging system

    Science.gov (United States)

    Li, Zhijun; Chen, Xing Long

    2016-10-01

    In the spectral imaging system, random jitter and posture change of the aircraft generated random image motion, and flight of aircraft caused forward image motion. Both of image motion can cause image blur in a longer exposure time, which need for image motion compensation. Due to limited field of view of the optical system, limited size and weight, a stable FSM (Fast Steering Mirror) was used for random image motion compensation and a compensation FSM was used for forward image motion compensation. In the random image motion compensation, inertial sensors were used for measuring the random jitter and the posture change of the aircraft. As the advantages and disadvantages for the gyroscope and inclinometer, we used data fusion of the two sensors to complementary advantages with closed-loop mode filter data based on the frequency domain. In this way, we got high linearity, little drift, high bandwidth and little electrical noise inertial measurement sensors. On the other hand, the motion of the compensation mirror was broken down to the amount of displacement within the time required for each interrupt movement. Under strict timing control, macro forward image motion compensation was realized in the exposure time. The above image motion compensation methods were applied to actual spectral imaging systems, aerial experiment results show that image motion compensation obtained good results and met the remaining image motion compensation image error was not more than 1/3 pixel.

  18. The spectral imaging facility: Setup characterization

    Energy Technology Data Exchange (ETDEWEB)

    De Angelis, Simone, E-mail: simone.deangelis@iaps.inaf.it; De Sanctis, Maria Cristina; Manzari, Paola Olga [Institute for Space Astrophysics and Planetology, INAF-IAPS, Via Fosso del Cavaliere, 100, 00133 Rome (Italy); Ammannito, Eleonora [Institute for Space Astrophysics and Planetology, INAF-IAPS, Via Fosso del Cavaliere, 100, 00133 Rome (Italy); Department of Earth, Planetary and Space Sciences, University of California, Los Angeles, Los Angeles, California 90095-1567 (United States); Di Iorio, Tatiana [ENEA, UTMEA-TER, Rome (Italy); Liberati, Fabrizio [Opto Service SrL, Campagnano di Roma (RM) (Italy); Tarchi, Fabio; Dami, Michele; Olivieri, Monica; Pompei, Carlo [Selex ES, Campi Bisenzio (Italy); Mugnuolo, Raffaele [Italian Space Agency, ASI, Spatial Geodesy Center, Matera (Italy)

    2015-09-15

    The SPectral IMager (SPIM) facility is a laboratory visible infrared spectrometer developed to support space borne observations of rocky bodies of the solar system. Currently, this laboratory setup is used to support the DAWN mission, which is in its journey towards the asteroid 1-Ceres, and to support the 2018 Exo-Mars mission in the spectral investigation of the Martian subsurface. The main part of this setup is an imaging spectrometer that is a spare of the DAWN visible infrared spectrometer. The spectrometer has been assembled and calibrated at Selex ES and then installed in the facility developed at the INAF-IAPS laboratory in Rome. The goal of SPIM is to collect data to build spectral libraries for the interpretation of the space borne and in situ hyperspectral measurements of planetary materials. Given its very high spatial resolution combined with the imaging capability, this instrument can also help in the detailed study of minerals and rocks. In this paper, the instrument setup is first described, and then a series of test measurements, aimed to the characterization of the main subsystems, are reported. In particular, laboratory tests have been performed concerning (i) the radiation sources, (ii) the reference targets, and (iii) linearity of detector response; the instrumental imaging artifacts have also been investigated.

  19. "Conventional" CT images from spectral measurements

    Science.gov (United States)

    Rajbhandary, Paurakh L.; Pelc, Norbert J.

    2016-03-01

    Spectral imaging systems need to be able to produce "conventional" images, and it's been shown that systems with energy discriminating detectors can achieve higher CNR than conventional systems by optimal weighting. Combining measured data in energy bins (EBs) and also combining basis material images have previously been proposed, but there are no studies systematically comparing the two methods. In this paper, we analytically evaluate the two methods for systems with ideal photon counting detectors using CNR and beam hardening (BH) artifact as metrics. For a 120-kVp polychromatic simulations of a water phantom with low contrast inserts, the difference of the optimal CNR between the two methods for the studied phantom is within 2%. For a polychromatic spectrum, beam-hardening artifacts are noticeable in EB weighted images (BH artifact of 3.8% for 8 EB and 6.9% for 2 EB), while weighted basis material images are free of such artifacts.

  20. Laser Imaging of Airborne Acoustic Emission by Nonlinear Defects

    Science.gov (United States)

    Solodov, Igor; Döring, Daniel; Busse, Gerd

    2008-06-01

    Strongly nonlinear vibrations of near-surface fractured defects driven by an elastic wave radiate acoustic energy into adjacent air in a wide frequency range. The variations of pressure in the emitted airborne waves change the refractive index of air thus providing an acoustooptic interaction with a collimated laser beam. Such an air-coupled vibrometry (ACV) is proposed for detecting and imaging of acoustic radiation of nonlinear spectral components by cracked defects. The photoelastic relation in air is used to derive induced phase modulation of laser light in the heterodyne interferometer setup. The sensitivity of the scanning ACV to different spatial components of the acoustic radiation is analyzed. The animated airborne emission patterns are visualized for the higher harmonic and frequency mixing fields radiated by planar defects. The results confirm a high localization of the nonlinear acoustic emission around the defects and complicated directivity patterns appreciably different from those observed for fundamental frequencies.

  1. Correlation image velocimetry: a spectral approach

    Science.gov (United States)

    Roux, Stéphane; Hild, François; Berthaud, Yves

    2002-01-01

    A method, believed to be new, is introduced to evaluate displacement fields from the analysis of a deformed image compared with a reference image. In contrast to standard methods, which determine a piecewise constant displacement field, the present method gives direct access to spectral decomposition of the displacement field. A minimization procedure is derived and used twice: first, to determine an affine displacement field and, then, the spectral components of the residual displacement. Although the method is applicable to any space dimension, only cases dealing with one-dimensional signals are reported: First, a purely synthetic example is discussed to estimate the intrinsic performance of the method, and a second case deals with a profile extracted from a sample of compressed glass wool.

  2. CONSTRAINED SPECTRAL CLUSTERING FOR IMAGE SEGMENTATION

    Science.gov (United States)

    Sourati, Jamshid; Brooks, Dana H.; Dy, Jennifer G.; Erdogmus, Deniz

    2013-01-01

    Constrained spectral clustering with affinity propagation in its original form is not practical for large scale problems like image segmentation. In this paper we employ novelty selection sub-sampling strategy, besides using efficient numerical eigen-decomposition methods to make this algorithm work efficiently for images. In addition, entropy-based active learning is also employed to select the queries posed to the user more wisely in an interactive image segmentation framework. We evaluate the algorithm on general and medical images to show that the segmentation results will improve using constrained clustering even if one works with a subset of pixels. Furthermore, this happens more efficiently when pixels to be labeled are selected actively. PMID:24466500

  3. Dynamical Imaging using Spatial Nonlinearity

    Science.gov (United States)

    2014-01-29

    Imin )/ (Imax + Imin ) = 0.15 for detection of the bars (from maxima to central dip). For our experimental measurements, the best linear visibility is...Statistical theory for incoherent light propagation in nonlinear media, Physical Review E, 65 (2002) 035602. [52] M.J. Bastiaans, Application of the...1238. [53] M.E. Testorf, B.M. Hennelly, J. Ojeda-Castañeda, Phase-space optics : fundamentals and applications , McGraw-Hill, New York, 2010. [54] K.H

  4. Nonlinear susceptibility magnitude imaging of magnetic nanoparticles

    Science.gov (United States)

    Ficko, Bradley W.; Giacometti, Paolo; Diamond, Solomon G.

    2015-03-01

    This study demonstrates a method for improving the resolution of susceptibility magnitude imaging (SMI) using spatial information that arises from the nonlinear magnetization characteristics of magnetic nanoparticles (mNPs). In this proof-of-concept study of nonlinear SMI, a pair of drive coils and several permanent magnets generate applied magnetic fields and a coil is used as a magnetic field sensor. Sinusoidal alternating current (AC) in the drive coils results in linear mNP magnetization responses at primary frequencies, and nonlinear responses at harmonic frequencies and intermodulation frequencies. The spatial information content of the nonlinear responses is evaluated by reconstructing tomographic images with sequentially increasing voxel counts using the combined linear and nonlinear data. Using the linear data alone it is not possible to accurately reconstruct more than 2 voxels with a pair of drive coils and a single sensor. However, nonlinear SMI is found to accurately reconstruct 12 voxels (R2=0.99, CNR=84.9) using the same physical configuration. Several time-multiplexing methods are then explored to determine if additional spatial information can be obtained by varying the amplitude, phase and frequency of the applied magnetic fields from the two drive coils. Asynchronous phase modulation, amplitude modulation, intermodulation phase modulation, and frequency modulation all resulted in accurate reconstruction of 6 voxels (R2>0.9) indicating that time multiplexing is a valid approach to further increase the resolution of nonlinear SMI. The spatial information content of nonlinear mNP responses and the potential for resolution enhancement with time multiplexing demonstrate the concept and advantages of nonlinear SMI.

  5. Image denoising using modified nonlinear diffusion approach

    Science.gov (United States)

    Upadhyay, Akhilesh R.; Talbar, Sanjay N.; Sontakke, Trimbak R.

    2006-01-01

    Partial Differential Equation (PDE) based, non-linear diffusion approaches are an effective way to denoise the images. In this paper, the work is extended to include anisotropic diffusion, where the diffusivity is a tensor valued function, which can be adapted to local edge orientation. This allows smoothing along the edges, but not perpendicular to it. The diffusion tensor is a function of differential structure of the evolving image itself. Such a feedback leads to nonlinear diffusion filters. It shows improved performance in the presence of noise. The original anisotropic diffusion algorithm updates each point based on four nearest-neighbor differences, the progress of diffusion results in improved edges. In the proposed method the edges are better preserved because diffusion is controlled by the gray level differences of diagonal neighbors in addition to 4 nearest neighbors using coupled PDF formulation. The proposed algorithm gives excellent results for MRI images, Biomedical images and Fingerprint images with noise.

  6. Nonlinear inverse synthesis for high spectral efficiency transmission in optical fibers

    CERN Document Server

    Le, Son Thai; Turitsyn, Sergei K

    2014-01-01

    In linear communication channels, spectral components (modes) defined by the Fourier transform of the signal propagate without interactions with each other. In certain nonlinear channels, such as the one modelled by the classical nonlinear Schr\\"odinger equation, there are nonlinear modes (nonlinear signal spectrum) that also propagate without interacting with each other and without corresponding nonlinear cross talk; effectively, in a linear manner. Here, we describe in a constructive way how to introduce such nonlinear modes for a given input signal. We investigate the performance of the nonlinear inverse synthesis (NIS) method, in which the information is encoded directly onto the continuous part of the nonlinear signal spectrum. This transmission technique, combined with the appropriate distributed Raman amplification, can provide an effective eigenvalue division multiplexing with high spectral efficiency, thanks to highly suppressed channel cross talk. The proposed NIS approach can be integrated with any...

  7. Ultrafast Imaging using Spectral Resonance Modulation.

    Science.gov (United States)

    Huang, Eric; Ma, Qian; Liu, Zhaowei

    2016-04-28

    CCD cameras are ubiquitous in research labs, industry, and hospitals for a huge variety of applications, but there are many dynamic processes in nature that unfold too quickly to be captured. Although tradeoffs can be made between exposure time, sensitivity, and area of interest, ultimately the speed limit of a CCD camera is constrained by the electronic readout rate of the sensors. One potential way to improve the imaging speed is with compressive sensing (CS), a technique that allows for a reduction in the number of measurements needed to record an image. However, most CS imaging methods require spatial light modulators (SLMs), which are subject to mechanical speed limitations. Here, we demonstrate an etalon array based SLM without any moving elements that is unconstrained by either mechanical or electronic speed limitations. This novel spectral resonance modulator (SRM) shows great potential in an ultrafast compressive single pixel camera.

  8. Theoretical aspects of nonlinear echo image system

    Institute of Scientific and Technical Information of China (English)

    ZHANG Ruiquan; FENG Shaosong

    2003-01-01

    In order to develop the nonlinear echo image system to diagnose pathological changes in biological tissue , a simple physical model to analyse the character of nonlinear reflected wave in biological medium is postulated. The propagation of large amplitude plane sound wave in layered biological media is analysed for the one dimensional case by the method of successive approximation and the expression for the second order wave reflected from any interface of layered biological media is obtained. The relations between the second order reflection coefficients and the nonlinear parameters of medium below the interface are studied in three layers interfaces. Finally, the second order reflection coefficients of four layered media are calculated numerically. The results indicate that the nonlinear parameter B/A of each layer of biological media can be determined by the reflection method.

  9. Label-free nonlinear optical imaging of mouse retina.

    Science.gov (United States)

    He, Sicong; Ye, Cong; Sun, Qiqi; Leung, Christopher K S; Qu, Jianan Y

    2015-03-01

    A nonlinear optical (NLO) microscopy system integrating stimulated Raman scattering (SRS), two-photon excited fluorescence (TPEF) and second-harmonic generation (SHG) was developed to image fresh mouse retinas. The morphological and functional details of various retinal layers were revealed by the endogenous NLO signals. Particularly, high resolution label-free imaging of retinal neurons and nerve fibers in the ganglion cell and nerve fiber layers was achieved by capturing endogenous SRS and TPEF signals. In addition, the spectral and temporal analysis of TPEF images allowed visualization of different fluorescent components in the retinal pigment epithelium (RPE). Fluorophores with short TPEF lifetime, such as A2E, can be differentiated from other long-lifetime components in the RPE. The NLO imaging method would provide important information for investigation of retinal ganglion cell degeneration and holds the potential to study the biochemical processes of visual cycle in the RPE.

  10. Validation of spectral sky radiance derived from all-sky camera images – a case study

    Directory of Open Access Journals (Sweden)

    K. Tohsing

    2014-01-01

    Full Text Available Spectral sky radiance (380–760 nm is derived from measurements with a Hemispherical Sky Imager (HSI system. The HSI consists of a commercial compact CCD (charge coupled device camera equipped with a fish-eye lens and provides hemispherical sky images in three reference bands such as red, green and blue. To obtain the spectral sky radiance from these images non-linear regression functions for various sky conditions have been derived. The camera-based spectral sky radiance was validated by spectral sky radiance measured with a CCD spectroradiometer. The spectral sky radiance for complete distribution over the hemisphere between both instruments deviates by less than 20% at 500 nm for all sky conditions and for zenith angles less than 80°. The reconstructed spectra of the wavelength 380 nm to 760 nm between both instruments at various directions deviate by less then 20% for all sky conditions.

  11. Validation of spectral sky radiance derived from all-sky camera images – a case study

    Directory of Open Access Journals (Sweden)

    K. Tohsing

    2014-07-01

    Full Text Available Spectral sky radiance (380–760 nm is derived from measurements with a hemispherical sky imager (HSI system. The HSI consists of a commercial compact CCD (charge coupled device camera equipped with a fish-eye lens and provides hemispherical sky images in three reference bands such as red, green and blue. To obtain the spectral sky radiance from these images, non-linear regression functions for various sky conditions have been derived. The camera-based spectral sky radiance was validated using spectral sky radiance measured with a CCD spectroradiometer. The spectral sky radiance for complete distribution over the hemisphere between both instruments deviates by less than 20% at 500 nm for all sky conditions and for zenith angles less than 80°. The reconstructed spectra of the wavelengths 380–760 nm between both instruments at various directions deviate by less than 20% for all sky conditions.

  12. Spectrally Adaptable Compressive Sensing Imaging System

    Science.gov (United States)

    2014-05-01

    viewed by a Stingray F-033C CCD Color Camera. The desired bands are depicted in (g). The original desired bands are shown in (a). Reconstructed images...would be viewed by a Stingray F-033C CCD Color Camera. The desired bands are indicated in (e). The original desired bands are shown in (a). Reconstructed...times and the mean PSNR is estimated. The resulting spectral data cubes are shown as they would be viewed by a Stingray F-033C CCD Color Camera. Figure

  13. Nonlinear Laplacian spectral analysis of Rayleigh-Bénard convection

    Science.gov (United States)

    Brenowitz, N. D.; Giannakis, D.; Majda, A. J.

    2016-06-01

    The analysis of physical datasets using modern methods developed in machine learning presents unique challenges and opportunities. These datasets typically feature many degrees of freedom, which tends to increase the computational cost of statistical methods and complicate interpretation. In addition, physical systems frequently exhibit a high degree of symmetry that should be exploited by any data analysis technique. The classic problem of Rayleigh Benárd convection in a periodic domain is an example of such a physical system with trivial symmetries. This article presents a technique for analyzing the time variability of numerical simulations of two-dimensional Rayleigh-Bénard convection at large aspect ratio and intermediate Rayleigh number. The simulated dynamics are highly unsteady and consist of several convective rolls that are distributed across the domain and oscillate with a preferred frequency. Intermittent extreme events in the net heat transfer, as quantified by the time-weighted probability distribution function of the Nusselt number, are a hallmark of these simulations. Nonlinear Laplacian Spectral Analysis (NLSA) is a data-driven method which is ideally suited for the study of such highly nonlinear and intermittent dynamics, but the trivial symmetries of the Rayleigh-Bénard problem such as horizontal shift-invariance can mask the interesting dynamics. To overcome this issue, the vertical velocity is averaged over parcels of similar temperature and height, which substantially compresses the size of the dataset and removes trivial horizontal symmetries. This isothermally averaged dataset, which is shown to preserve the net convective heat-flux across horizontal surfaces, is then used as an input to NLSA. The analysis generates a small number of orthogonal modes which describe the spatiotemporal variability of the heat transfer. A regression analysis shows that the extreme events of the net heat transfer are primarily associated with a family of

  14. Nonlinear ultrasound imaging of nanoscale acoustic biomolecules

    Science.gov (United States)

    Maresca, David; Lakshmanan, Anupama; Lee-Gosselin, Audrey; Melis, Johan M.; Ni, Yu-Li; Bourdeau, Raymond W.; Kochmann, Dennis M.; Shapiro, Mikhail G.

    2017-02-01

    Ultrasound imaging is widely used to probe the mechanical structure of tissues and visualize blood flow. However, the ability of ultrasound to observe specific molecular and cellular signals is limited. Recently, a unique class of gas-filled protein nanostructures called gas vesicles (GVs) was introduced as nanoscale (˜250 nm) contrast agents for ultrasound, accompanied by the possibilities of genetic engineering, imaging of targets outside the vasculature and monitoring of cellular signals such as gene expression. These possibilities would be aided by methods to discriminate GV-generated ultrasound signals from anatomical background. Here, we show that the nonlinear response of engineered GVs to acoustic pressure enables selective imaging of these nanostructures using a tailored amplitude modulation strategy. Finite element modeling predicted a strongly nonlinear mechanical deformation and acoustic response to ultrasound in engineered GVs. This response was confirmed with ultrasound measurements in the range of 10 to 25 MHz. An amplitude modulation pulse sequence based on this nonlinear response allows engineered GVs to be distinguished from linear scatterers and other GV types with a contrast ratio greater than 11.5 dB. We demonstrate the effectiveness of this nonlinear imaging strategy in vitro, in cellulo, and in vivo.

  15. Baseline-free fatigue crack detection based on spectral correlation and nonlinear wave modulation

    Science.gov (United States)

    Liu, Peipei; Sohn, Hoon; Yang, Suyoung; Lim, Hyung Jin

    2016-12-01

    By generating ultrasonic waves at two different frequencies onto a cracked structure, modulations due to crack-induced nonlinearity can be observed in the corresponding ultrasonic response. This nonlinear wave modulation phenomenon has been widely studied and proven capable of detecting a fatigue crack at a very early stage. However, under field conditions, other exogenous vibrations exist and the modulation components can be buried under ambient noises, making it difficult to extract the modulation components simply by using a spectral density function. In this study, the nonlinear modulation components in the ultrasonic response were extracted using a spectral correlation function (the double Fourier transform) with respect to time and time lag of a signal’s autocorrelation. Using spectral correlation, noise or interference, which is spectrally overlapped with the nonlinear modulation components in the ultrasonic response, can be effectively removed or reduced. Only the nonlinear modulation components are accentuated at specific coordinates of the spectral correlation plot. A damage feature is defined by comparing the spectral correlation value between nonlinear modulation components with other spectral correlation values among randomly selected frequencies. Then, by analyzing the statistical characteristics of the multiple damage feature values obtained from different input frequency combinations, fatigue cracks can be detected without relying on baseline data obtained from the pristine condition of the target structure. In the end, an experimental test was conducted on aluminum plates with a real fatigue crack and the test signals were contaminated by simulated noises with varying signal-to-noise ratios. The results validated the proposed technique.

  16. ADVANCES IN HYPERSPECTRAL AND MULTISPECTRAL IMAGE FUSION AND SPECTRAL UNMIXING

    OpenAIRE

    C. Lanaras; E. Baltsavias; K. Schindler

    2015-01-01

    In this work, we jointly process high spectral and high geometric resolution images and exploit their synergies to (a) generate a fused image of high spectral and geometric resolution; and (b) improve (linear) spectral unmixing of hyperspectral endmembers at subpixel level w.r.t. the pixel size of the hyperspectral image. We assume that the two images are radiometrically corrected and geometrically co-registered. The scientific contributions of this work are (a) a simultaneous approa...

  17. Spectral phasor analysis allows rapid and reliable unmixing of fluorescence microscopy spectral images

    NARCIS (Netherlands)

    Fereidouni, F.; Bader, A.N.; Gerritsen, H.C.

    2012-01-01

    A new global analysis algorithm to analyse (hyper-) spectral images is presented. It is based on the phasor representation that has been demonstrated to be very powerful for the analysis of lifetime imaging data. In spectral phasor analysis the fluorescence spectrum of each pixel in the image is Fou

  18. Precise acquisition and unsupervised segmentation of multi-spectral images

    DEFF Research Database (Denmark)

    Gomez, David Delgado; Clemmensen, Line Katrine Harder; Ersbøll, Bjarne Kjær

    2007-01-01

    In this work, an integrated imaging system to obtain accurate and reproducible multi-spectral images and a novel multi-spectral image segmentation algorithm are proposed. The system collects up to 20 different spectral bands within a range that vary from 395 nm to 970 nm. The system is designed...... to acquire geometrically and chromatically corrected images in homogeneous and diffuse illumination, so images can be compared over time. The proposed segmentation algorithm combines the information provided by all the spectral bands to segment the different regions of interest. Three experiments...

  19. Extended arrays for nonlinear susceptibility magnitude imaging

    Science.gov (United States)

    Ficko, Bradley W.; Giacometti, Paolo; Diamond, Solomon G.

    2016-01-01

    This study implements nonlinear susceptibility magnitude imaging (SMI) with multifrequency intermodulation and phase encoding. An imaging grid was constructed of cylindrical wells of 3.5-mm diameter and 4.2-mm height on a hexagonal two-dimensional 61-voxel pattern with 5-mm spacing. Patterns of sample wells were filled with 40-μl volumes of Fe3O4 starch-coated magnetic nanoparticles (mNPs) with a hydrodynamic diameter of 100 nm and a concentration of 25 mg/ml. The imaging hardware was configured with three excitation coils and three detection coils in anticipation that a larger imaging system will have arrays of excitation and detection coils. Hexagonal and bar patterns of mNP were successfully imaged (R2 > 0.9) at several orientations. This SMI demonstration extends our prior work to feature a larger coil array, enlarged field-of-view, effective phase encoding scheme, reduced mNP sample size, and more complex imaging patterns to test the feasibility of extending the method beyond the pilot scale. The results presented in this study show that nonlinear SMI holds promise for further development into a practical imaging system for medical applications. PMID:26124044

  20. Control and Detection of Discrete Spectral Amplitudes in Nonlinear Fourier Spectrum

    CERN Document Server

    Aref, Vahid

    2016-01-01

    Nonlinear Fourier division Multiplexing (NFDM) can be realized from modulating the discrete nonlinear spectrum of an $N$-solitary waveform. To generate an $N$-solitary waveform from desired discrete spectrum (eigenvalue and discrete spectral amplitudes), we use the Darboux Transform. We explain how to the norming factors must be set in order to have the desired discrete spectrum. To derive these norming factors, we study the evolution of nonlinear spectrum by adding a new eigenvalue and its spectral amplitude. We further simplify the Darboux transform algorithm. We propose a novel algorithm (to the best of our knowledge) to numerically compute the nonlinear Fourier Transform (NFT) of a given pulse. The NFT algorithm, called forward-backward method, is based on splitting the signal into two parts and computing the nonlinear spectrum of each part from boundary ($\\pm\\infty$) inward. The nonlinear spectrum (discrete and continuous) derived from efficiently combining both parts has a promising numerical precision....

  1. Spectral Camera based on Ghost Imaging via Sparsity Constraints

    Science.gov (United States)

    Liu, Zhentao; Tan, Shiyu; Wu, Jianrong; Li, Enrong; Shen, Xia; Han, Shensheng

    2016-05-01

    The image information acquisition ability of a conventional camera is usually much lower than the Shannon Limit since it does not make use of the correlation between pixels of image data. Applying a random phase modulator to code the spectral images and combining with compressive sensing (CS) theory, a spectral camera based on true thermal light ghost imaging via sparsity constraints (GISC spectral camera) is proposed and demonstrated experimentally. GISC spectral camera can acquire the information at a rate significantly below the Nyquist rate, and the resolution of the cells in the three-dimensional (3D) spectral images data-cube can be achieved with a two-dimensional (2D) detector in a single exposure. For the first time, GISC spectral camera opens the way of approaching the Shannon Limit determined by Information Theory in optical imaging instruments.

  2. Spectral Camera based on Ghost Imaging via Sparsity Constraints.

    Science.gov (United States)

    Liu, Zhentao; Tan, Shiyu; Wu, Jianrong; Li, Enrong; Shen, Xia; Han, Shensheng

    2016-05-16

    The image information acquisition ability of a conventional camera is usually much lower than the Shannon Limit since it does not make use of the correlation between pixels of image data. Applying a random phase modulator to code the spectral images and combining with compressive sensing (CS) theory, a spectral camera based on true thermal light ghost imaging via sparsity constraints (GISC spectral camera) is proposed and demonstrated experimentally. GISC spectral camera can acquire the information at a rate significantly below the Nyquist rate, and the resolution of the cells in the three-dimensional (3D) spectral images data-cube can be achieved with a two-dimensional (2D) detector in a single exposure. For the first time, GISC spectral camera opens the way of approaching the Shannon Limit determined by Information Theory in optical imaging instruments.

  3. Spectral Image Analysis for Measuring Ripeness of Tomatoes

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.

    2002-01-01

    In this study, spectral images of five ripeness stages of tomatoes have been recorded and analyzed. The electromagnetic spectrum between 396 and 736 nm was recorded in 257 bands (every 1.3 nm). Results show that spectral images offer more discriminating power than standard RGB images for measuring r

  4. Enhancing retinal images by nonlinear registration

    CERN Document Server

    Molodij, Guillaume; Glanc, Marie; Chenegros, Guillaume

    2014-01-01

    Being able to image the human retina in high resolution opens a new era in many important fields, such as pharmacological research for retinal diseases, researches in human cognition, nervous system, metabolism and blood stream, to name a few. In this paper, we propose to share the knowledge acquired in the fields of optics and imaging in solar astrophysics in order to improve the retinal imaging at very high spatial resolution in the perspective to perform a medical diagnosis. The main purpose would be to assist health care practitioners by enhancing retinal images and detect abnormal features. We apply a nonlinear registration method using local correlation tracking to increase the field of view and follow structure evolutions using correlation techniques borrowed from solar astronomy technique expertise. Another purpose is to define the tracer of movements after analyzing local correlations to follow the proper motions of an image from one moment to another, such as changes in optical flows that would be o...

  5. Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2016-03-01

    Electromagnetic imaging is the problem of determining material properties from scattered fields measured away from the domain under investigation. Solving this inverse problem is a challenging task because (i) it is ill-posed due to the presence of (smoothing) integral operators used in the representation of scattered fields in terms of material properties, and scattered fields are obtained at a finite set of points through noisy measurements; and (ii) it is nonlinear simply due the fact that scattered fields are nonlinear functions of the material properties. The work described in this thesis tackles the ill-posedness of the electromagnetic imaging problem using sparsity-based regularization techniques, which assume that the scatterer(s) occupy only a small fraction of the investigation domain. More specifically, four novel imaging methods are formulated and implemented. (i) Sparsity-regularized Born iterative method iteratively linearizes the nonlinear inverse scattering problem and each linear problem is regularized using an improved iterative shrinkage algorithm enforcing the sparsity constraint. (ii) Sparsity-regularized nonlinear inexact Newton method calls for the solution of a linear system involving the Frechet derivative matrix of the forward scattering operator at every iteration step. For faster convergence, the solution of this matrix system is regularized under the sparsity constraint and preconditioned by leveling the matrix singular values. (iii) Sparsity-regularized nonlinear Tikhonov method directly solves the nonlinear minimization problem using Landweber iterations, where a thresholding function is applied at every iteration step to enforce the sparsity constraint. (iv) This last scheme is accelerated using a projected steepest descent method when it is applied to three-dimensional investigation domains. Projection replaces the thresholding operation and enforces the sparsity constraint. Numerical experiments, which are carried out using

  6. Spectral imaging of galaxy clusters with Planck

    CERN Document Server

    Bourdin, H; Rasia, E

    2016-01-01

    The Sunyaev-Zeldovich (SZ) effect is a promising tool for detecting the presence of hot gas out to the galaxy cluster peripheries. We developed a spectral imaging algorithm dedicated to the SZ observations of nearby galaxy clusters with Planck, with the aim of revealing gas density anisotropies related to the filamentary accretion of materials, or pressure discontinuities induced by the propagation of shock fronts. To optimize an unavoidable trade-off between angular resolution and precision of the SZ flux measurements, the algorithm performs a multiscale analysis of the SZ maps as well as of other extended components, such as the cosmic microwave background (CMB) anisotropies and the Galactic thermal dust. The demixing of the SZ signal is tackled through kernel weighted likelihood maximizations. The CMB anisotropies are further analyzed through a wavelet analysis, while the Galactic foregrounds and SZ maps are analyzed via a curvelet analysis that best preserves their anisotropic details. The algorithm perfo...

  7. Spectral properties of a confined nonlinear quantum oscillator in one and three dimensions

    Energy Technology Data Exchange (ETDEWEB)

    Schulze-Halberg, Axel; Gordon, Christopher R. [Department of Mathematics and Actuarial Science, Indiana University Northwest, 3400 Broadway, Gary, Indiana 46408 (United States)

    2013-04-15

    We analyze the spectral behaviour of a nonlinear quantum oscillator model under confinement. The underlying potential is given by a harmonic oscillator interaction plus a nonlinear term that can be weakened or strengthened through a parameter. Numerical eigenvalues of the model in one and three dimensions are presented. The asymptotic behaviour of the eigenvalues for confinement relaxation and for vanishing nonlinear term in the potential is investigated. Our findings are compared with existing results.

  8. The power spectral density of digital modulations transmitted over nonlinear channels

    Science.gov (United States)

    Divsalar, D.; Simon, M. K.

    1982-01-01

    This paper examines by analytical methods the power spectral densities of digital modulations (in particular, staggered and unstaggered quadrature modulations) passed through band-limited nonlinear channels. Previously observed (by computer simulation or hardware measurement) behavior of such spectra with regard to the suppression or restoration of its sidelobes after passing through the nonlinearity is verified analytically. Several examples corresponding to specific quadrature modulations and filter-nonlinearity combinations are presented as illustrations of the general results.

  9. Nonlinear spectral and lifetime management in upconversion nanoparticles by controlling energy distribution.

    Science.gov (United States)

    Wang, Yu; Deng, Renren; Xie, Xiaoji; Huang, Ling; Liu, Xiaogang

    2016-03-28

    Optical tuning of lanthanide-doped upconversion nanoparticles has attracted considerable attention over the past decade because this development allows the advance of new frontiers in energy conversion, materials science, and biological imaging. Here we present a rational approach to manipulating the spectral profile and lifetime of lanthanide emission in upconversion nanoparticles by tailoring their nonlinear optical properties. We demonstrate that the incorporation of energy distributors, such as surface defects or an extra amount of dopants, into a rare-earth-based host lattice alters the decay behavior of excited sensitizers, thus markedly improving the emitters' sensitivity to excitation power. This work provides insight into mechanistic understanding of upconversion phenomena in nanoparticles and also enables exciting new opportunities of using these nanomaterials for photonic applications.

  10. Spectral methods for spatial resolution improvement of digital images

    Institute of Scientific and Technical Information of China (English)

    郝鹏威; 徐冠华; 朱重光

    1999-01-01

    A general matrix formula is proposed for signal spectral aliasing of various or mutual resolution, the concept of spectral aliasing matrix is introduced, and some general spectral methods for spatial resolution improvement from multiframes of undersampled digital images are discussed. A simplified iterative method of parallel row-action projection for spectral de-aliasing is also given. The method can be applied to multiframe images with various spatial resolution,relative displacement, dissimilar point spread function, different image radiance, and additive random noise. Some experiments with a resolution test pattern and an image of vertical fin performed the convergence and the effectiveness of the algorithms.

  11. Enhanced nonlinear imaging through scattering media using transmission matrix based wavefront shaping

    CERN Document Server

    de Aguiar, Hilton B; Brasselet, Sophie

    2016-01-01

    Despite the tremendous progresses in wavefront control through or inside complex scattering media, several limitations prevent reaching practical feasibility for nonlinear imaging in biological tissues. While the optimization of nonlinear signals might suffer from low signal to noise conditions and from possible artifacts at large penetration depths, it has nevertheless been largely used in the multiple scattering regime since it provides a guide star mechanism as well as an intrinsic compensation for spatiotemporal distortions. Here, we demonstrate the benefit of Transmission Matrix (TM) based approaches under broadband illumination conditions, to perform nonlinear imaging. Using ultrashort pulse illumination with spectral bandwidth comparable but still lower than the spectral width of the scattering medium, we show strong nonlinear enhancements of several orders of magnitude, through thicknesses of a few transport mean free paths, which corresponds to millimeters in biological tissues. Linear TM refocusing ...

  12. Spectral Analysis of Polynomial Nonlinearity with Applications to RF Power Amplifiers

    Directory of Open Access Journals (Sweden)

    G. Tong Zhou

    2004-09-01

    Full Text Available The majority of the nonlinearity in a communication system is attributed to the power amplifier (PA present at the final stage of the transmitter chain. In this paper, we consider Gaussian distributed input signals (such as OFDM, and PAs that can be modeled by memoryless or memory polynomials. We derive closed-form expressions of the PA output power spectral density, for an arbitrary nonlinear order, based on the so-called Leonov-Shiryaev formula. We then apply these results to answer practical questions such as the contribution of AM/PM conversion to spectral regrowth and the relationship between memory effects and spectral asymmetry.

  13. Nonlinear Polarimetric Microscopy for Biomedical Imaging

    Science.gov (United States)

    Samim, Masood

    A framework for the nonlinear optical polarimetry and polarimetric microscopy is developed. Mathematical equations are derived in terms of linear and nonlinear Stokes Mueller formalism, which comprehensively characterize the polarization properties of the incoming and outgoing radiations, and provide structural information about the organization of the investigated materials. The algebraic formalism developed in this thesis simplifies many predictions for a nonlinear polarimetry study and provides an intuitive understanding of various polarization properties for radiations and the intervening medium. For polarimetric microscopy experiments, a custom fast-scanning differential polarization microscope is developed, which is also capable of real-time three-dimensional imaging. The setup is equipped with a pair of high-speed resonant and galvanometric scanning mirrors, and supplemented by advanced adaptive optics and data acquisition modules. The scanning mirrors when combined with the adaptive optics deformable mirror enable fast 3D imaging. Deformable membrane mirrors and genetic algorithm optimization routines are employed to improve the imaging conditions including correcting the optical aberrations, maximizing signal intensities, and minimizing point-spread-functions of the focal volume. A field-programmable-gate array (FPGA) chip is exploited to rapidly acquire and process the multidimensional data. Using the nonlinear optical polarimetry framework and the home-built polarization microscope, a few biologically important tissues are measured and analyzed to gain insight as to their structure and dynamics. The structure and distribution of muscle sarcomere myosins, connective tissue collagen, carbohydrate-rich starch, and fruit fly eye retinal molecules are characterized with revealing polarization studies. In each case, using the theoretical framework, polarization sensitive data are analyzed to decipher the molecular orientations and nonlinear optical

  14. Spectral Camera based on Ghost Imaging via Sparsity Constraints

    CERN Document Server

    Liu, Zhentao; Wu, Jianrong; Li, Enrong; Shen, Xia; Han, Shensheng

    2015-01-01

    The information acquisition ability of conventional camera is far lower than the Shannon Limit because of the correlation between pixels of image data. Applying sparse representation of images to reduce the abundance of image data and combined with compressive sensing theory, the spectral camera based on ghost imaging via sparsity constraints (GISC spectral camera) is proposed and demonstrated experimentally. GISC spectral camera can acquire the information at a rate significantly below Nyquist, and the resolution of the cells in the three-dimensional (3D) spectral image data-cube can be achieved with a two-dimensional (2D) detector in a single exposure. For the first time, GISC spectral camera opens the way of approaching the Shannon Limit determined by Information Theory in optical imaging instruments.

  15. A New Multichannel Spectral Imaging Laser Scanning Confocal Microscope

    Directory of Open Access Journals (Sweden)

    Yunhai Zhang

    2013-01-01

    Full Text Available We have developed a new multichannel spectral imaging laser scanning confocal microscope for effective detection of multiple fluorescent labeling in the research of biological tissues. In this paper, the design and key technologies of the system are introduced. Representative results on confocal imaging, 3-dimensional sectioning imaging, and spectral imaging are demonstrated. The results indicated that the system is applicable to multiple fluorescent labeling in biological experiments.

  16. An improved numerical method for nonlinear terms of spectral model and its applications

    Institute of Scientific and Technical Information of China (English)

    2003-01-01

    At present, the spectral model is one of the most widely applied numerical models in the research of numerical prediction and climatic variation. To improve the precision and efficiency of spectral method can greatly contribute to the development of numerical prediction. As the core part of spectral method, the calculating method of nonlinear terms always concentrates on numerical solution of atmospheric dynamical processes in the spectral space. However, there was little study in this field in the late thirty years. According to the principle of nonlinear term calculation with the dimensionality degradation and latitudinal perfect spectral method, we designed a new nonlinear term calculating method and made it compatible well with the common numerical algorithms of the spectral model used internationally. With an own-designed spectral dynamical framework suiting for the numerical application in common uses, theoretical analyses and numerical experiments have also been deeply conducted to compare our new method with the widely-used transform method in an attempt to advance the development of numerical algorithms of spectral model.

  17. Integrated Spectral Low Noise Image Sensor with Nanowire Polarization Filters for Low Contrast Imaging

    Science.gov (United States)

    2015-11-05

    filters and investigate their integration with the spectral image sensors. In addition, I will investigate image processing algorithms that will take...are composed of a 2D grid of heterogeneous imaging sensors. Current polarization imaging employ four different pixelated polarization filters ... filters and investigate their integration with the spectral image sensors. In addition, I will investigate image processing algorithms that will take

  18. A Spectral Element Method for Nonlinear and Dispersive Water Waves

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Bigoni, Daniele; Eskilsson, Claes

    The use of flexible mesh discretisation methods are important for simulation of nonlinear wave-structure interactions in offshore and marine settings such as harbour and coastal areas. For real applications, development of efficient models for wave propagation based on unstructured discretisation...... methods is of key interest. We present a high-order general-purpose three-dimensional numerical model solving fully nonlinear and dispersive potential flow equations with a free surface.......The use of flexible mesh discretisation methods are important for simulation of nonlinear wave-structure interactions in offshore and marine settings such as harbour and coastal areas. For real applications, development of efficient models for wave propagation based on unstructured discretisation...

  19. Compact multi-spectral imaging system for dermatology and neurosurgery

    Science.gov (United States)

    Noordmans, Herke Jan; de Roode, Rowland; Verdaasdonk, Rudolf

    2007-03-01

    A compact multi-spectral imaging system is presented as diagnostic tool in dermatology and neurosurgery. Using an electronically tunable filter, a sensitive high resolution digital camera, 140 spectral images from 400 nm up to 720 nm are acquired in 40 s. Advanced image processing algorithms are used to enable interactive acquisition, viewing, image registration and image analysis. Experiments in the department of dermatology and neurosurgery show that multispectral imaging reveals much more detail than conventional medical photography or a surgical microscope, as images can be reprocessed to enhance the view on e.g. tumor boundaries. Using a hardware-based interactive registration algorithm, multi-spectral images can be aligned to correct for motion occurred during image acquisition or to compare acquisitions from different moments in time. The system shows to be a powerful diagnostics tool for medical imaging in the visual and near IR range.

  20. Maximum a posteriori estimation of spectral reflectance from color image and multipoint spectral measurements.

    Science.gov (United States)

    Murakami, Yuri; Ietomi, Kunihiko; Yamaguchi, Masahiro; Ohyama, Nagaaki

    2007-10-01

    Accurate color image reproduction under arbitrary illumination can be realized if the spectral reflectance functions in a scene are obtained. Although multispectral imaging is one of the promising methods to obtain the reflectance of a scene, it is expected to reduce the number of color channels without significant loss of accuracy. This paper presents what we believe to be a new method for estimating spectral reflectance functions from color image and multipoint spectral measurements based on maximum a posteriori (MAP) estimation. Multipoint spectral measurements are utilized as auxiliary information to improve the accuracy of spectral reflectance estimated from image data. Through simulations, it is confirmed that the proposed method improves the estimation accuracy, particularly when a scene includes subjects that belong to various categories.

  1. SPECTRAL IMAGING OF GALAXY CLUSTERS WITH PLANCK

    Energy Technology Data Exchange (ETDEWEB)

    Bourdin, H.; Mazzotta, P. [Dipartimento di Fisica, Università degli Studi di Roma “Tor Vergata,” via della Ricerca Scientifica, 1, I-00133 Roma (Italy); Rasia, E., E-mail: herve.bourdin@roma2.infn.it [INAF-Osservatorio Astronomico of Trieste, via Tiepolo 11, I-34121 Trieste (Italy)

    2015-12-20

    The Sunyaev–Zeldovich (SZ) effect is a promising tool for detecting the presence of hot gas out to the galaxy cluster peripheries. We developed a spectral imaging algorithm dedicated to the SZ observations of nearby galaxy clusters with Planck, with the aim of revealing gas density anisotropies related to the filamentary accretion of materials, or pressure discontinuities induced by the propagation of shock fronts. To optimize an unavoidable trade-off between angular resolution and precision of the SZ flux measurements, the algorithm performs a multi-scale analysis of the SZ maps as well as of other extended components, such as the cosmic microwave background (CMB) anisotropies and the Galactic thermal dust. The demixing of the SZ signal is tackled through kernel-weighted likelihood maximizations. The CMB anisotropies are further analyzed through a wavelet analysis, while the Galactic foregrounds and SZ maps are analyzed via a curvelet analysis that best preserves their anisotropic details. The algorithm performance has been tested against mock observations of galaxy clusters obtained by simulating the Planck High Frequency Instrument and by pointing at a few characteristic positions in the sky. These tests suggest that Planck should easily allow us to detect filaments in the cluster peripheries and detect large-scale shocks in colliding galaxy clusters that feature favorable geometry.

  2. Unsupervised Post-Nonlinear Unmixing of Hyperspectral Images Using a Hamiltonian Monte Carlo Algorithm

    CERN Document Server

    Altmann, Yoann; Tourneret, Jean-Yves

    2013-01-01

    This paper presents a nonlinear mixing model for hyperspectral image unmixing. The proposed model assumes that the pixel reflectances are post-nonlinear functions of unknown pure spectral components contaminated by an additive white Gaussian noise. These nonlinear functions are approximated using polynomials leading to a polynomial post-nonlinear mixing model. A Bayesian algorithm is proposed to estimate the parameters involved in the model yielding an unsupervised nonlinear unmixing algorithm. Due to the large number of parameters to be estimated, an efficient Hamiltonian Monte Carlo algorithm is investigated. The classical leapfrog steps of this algorithm are modified to handle the parameter constraints. The performance of the unmixing strategy, including convergence and parameter tuning, is first evaluated on synthetic data. Simulations conducted with real data finally show the accuracy of the proposed unmixing strategy for the analysis of hyperspectral images.

  3. Unstructured Spectral Element Model for Dispersive and Nonlinear Wave Propagation

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Eskilsson, Claes; Bigoni, Daniele

    2016-01-01

    ). In the present paper we use a single layer of quadratic (in 2D) and prismatic (in 3D) elements. The model has been stabilized through a combination of over-integration of the Galerkin projections and a mild modal filter. We present numerical tests of nonlinear waves serving as a proof-of-concept validation...

  4. Spectral and modulational stability of periodic wavetrains for the nonlinear Klein-Gordon equation

    Science.gov (United States)

    Jones, Christopher K. R. T.; Marangell, Robert; Miller, Peter D.; Plaza, Ramón G.

    2014-12-01

    This paper is a detailed and self-contained study of the stability properties of periodic traveling wave solutions of the nonlinear Klein-Gordon equation utt-uxx+V‧(u)=0, where u is a scalar-valued function of x and t, and the potential V(u) is of class C2 and periodic. Stability is considered both from the point of view of spectral analysis of the linearized problem (spectral stability analysis) and from the point of view of wave modulation theory (the strongly nonlinear theory due to Whitham as well as the weakly nonlinear theory of wave packets). The aim is to develop and present new spectral stability results for periodic traveling waves, and to make a solid connection between these results and predictions of the (formal) modulation theory, which has been developed by others but which we review for completeness.

  5. Fast spectral color image segmentation based on filtering and clustering

    Science.gov (United States)

    Xing, Min; Li, Hongyu; Jia, Jinyuan; Parkkinen, Jussi

    2009-10-01

    This paper proposes a fast approach to spectral image segmentation. In the algorithm, two popular techniques are extended and applied to spectral color images: the mean-shift filtering and the kernel-based clustering. We claim that segmentation should be completed under illuminant F11 rather than directly using the original spectral reflectance, because such illumination can reduce data variability and expedite the following filtering. The modes obtained in the mean-shift filtering represent the local features of spectral images, and will be applied to segmentation in place of pixels. Since the modes are generally small in number, the eigendecomposition of kernel matrices, the crucial step in the kernelbased clustering, becomes much easier. The combination of these two techniques can efficiently enhance the performance of segmentation. Experiments show that the proposed segmentation method is feasible and very promising for spectral color images.

  6. Enhancing retinal images by nonlinear registration

    Science.gov (United States)

    Molodij, G.; Ribak, E. N.; Glanc, M.; Chenegros, G.

    2015-05-01

    Being able to image the human retina in high resolution opens a new era in many important fields, such as pharmacological research for retinal diseases, researches in human cognition, nervous system, metabolism and blood stream, to name a few. In this paper, we propose to share the knowledge acquired in the fields of optics and imaging in solar astrophysics in order to improve the retinal imaging in the perspective to perform a medical diagnosis. The main purpose would be to assist health care practitioners by enhancing the spatial resolution of the retinal images and increase the level of confidence of the abnormal feature detection. We apply a nonlinear registration method using local correlation tracking to increase the field of view and follow structure evolutions using correlation techniques borrowed from solar astronomy technique expertise. Another purpose is to define the tracer of movements after analyzing local correlations to follow the proper motions of an image from one moment to another, such as changes in optical flows that would be of high interest in a medical diagnosis.

  7. Graph Laplacian for spectral clustering and seeded image segmentation

    OpenAIRE

    Wallace Correa de Oliveira Casaca

    2014-01-01

    Image segmentation is an essential tool to enhance the ability of computer systems to efficiently perform elementary cognitive tasks such as detection, recognition and tracking. In this thesis we concentrate on the investigation of two fundamental topics in the context of image segmentation: spectral clustering and seeded image segmentation. We introduce two new algorithms for those topics that, in summary, rely on Laplacian-based operators, spectral graph theory, and minimization of energy f...

  8. SPECTRAL FILTRATION OF IMAGES BY MEANS OF DISPERSIVE SYSTEMS

    Directory of Open Access Journals (Sweden)

    I. M. Gulis

    2016-01-01

    Full Text Available Instruments for spectral filtration of images are an important element of the systems used in remote sensing, medical diagnostics, in-process measurements. The aim of this study is analysis of the functional features and characteristics of the proposed two image monochromator versions which are based on dispersive spectral filtering. The first is based on the use of a dispersive monochromator, where collimating and camera lenses form a telescopic system, the dispersive element of which is within the intermediate image plane. The second version is based on an imaging double monochromator with dispersion subtraction by back propagation. For the telescopic system version, the spectral and spatial resolutions are estimated, the latter being limited by aberrations and diffraction from the entrance slit. The device has been numerically simulated and prototyped. It is shown that for the spectral bandwidth 10 nm (visible spectral range, the aberration-limited spot size is from 10–20 μm at the image center to about 30 μm at the image periphery for the image size 23–27 mm. The monochromator with dispersion subtraction enables one to vary the spectral resolution (up to 1 nm and higher by changing the intermediate slit width. But the distinctive feature is a significant change in the selected central wavelength over the image field. The considered designs of dispersive image monochromators look very promising due to the particular advantages over the systems based on tunable filters as regards the spectral resolution, fast tuning, and the spectral contrast. The monochromator based on a telescopic system has a simple design and a rather large image field but it also has a limited light throughput due to small aperture size. The monochromator with dispersion subtraction has higher light throughput, can provide high spectral resolution when recording a full data cube in a series of measuring acts for different dispersive element positions. 

  9. Investigation of Image Fusion Between High-Resolution Image and Multi-spectral Image

    Institute of Scientific and Technical Information of China (English)

    LI Pingxiang; WANG Zhijun

    2003-01-01

    On the basis of a thorough understanding of the physical characteristics of remote sensing image, this paper employs the theories of wavelet transform and signal sampling to develop a new image fusion algorithm. The algorithm has been successfully applied to the image fusion of SPOT PAN and TM of Guangdong province, China. The experimental results show that a perfect image fusion can be built up by using the image analytical solution and re-construction in the image frequency domain based on the physical characteristics of the image formation. The method has demonstrated that the results of the image fusion do not change spectral characteristics of the original image.

  10. A stabilised nodal spectral element method for fully nonlinear water waves

    DEFF Research Database (Denmark)

    Engsig-Karup, Allan Peter; Eskilsson, C.; Bigoni, Daniele

    2016-01-01

    We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite element method proposed by Cai et al. (1998) [5], although...... the numerical implementation differs greatly. Features of the proposed spectral element method include: nodal Lagrange basis functions, a general quadrature-free approach and gradient recovery using global L2 projections. The quartic nonlinear terms present in the Zakharov form of the free surface conditions...

  11. Spectral ladar: towards active 3D multispectral imaging

    Science.gov (United States)

    Powers, Michael A.; Davis, Christopher C.

    2010-04-01

    In this paper we present our Spectral LADAR concept, an augmented implementation of traditional LADAR. This sensor uses a polychromatic source to obtain range-resolved 3D spectral images which are used to identify objects based on combined spatial and spectral features, resolving positions in three dimensions and up to hundreds of meters in distance. We report on a proof-of-concept Spectral LADAR demonstrator that generates spectral point clouds from static scenes. The demonstrator transmits nanosecond supercontinuum pulses generated in a photonic crystal fiber. Currently we use a rapidly tuned receiver with a high-speed InGaAs APD for 25 spectral bands with the future expectation of implementing a linear APD array spectrograph. Each spectral band is independently range resolved with multiple return pulse recognition. This is a critical feature, enabling simultaneous spectral and spatial unmixing of partially obscured objects when not achievable using image fusion of monochromatic LADAR and passive spectral imagers. This enables higher identification confidence in highly cluttered environments such as forested or urban areas (e.g. vehicles behind camouflage or foliage). These environments present challenges for situational awareness and robotic perception which can benefit from the unique attributes of Spectral LADAR. Results from this demonstrator unit are presented for scenes typical of military operations and characterize the operation of the device. The results are discussed here in the context of autonomous vehicle navigation and target recognition.

  12. Simultaneous measurements of nonlinear refraction and nonlinear absorption using a 4f imaging system

    Institute of Scientific and Technical Information of China (English)

    2008-01-01

    A method is reported to simultaneously measure the nonlinear absorption and re-fraction coefficients of materials using a nonlinear-imaging technique with a phase object. In this technique, the sign and magnitude of both the nonlinear absorption and refraction can be acquired conveniently from the analysis of three experiment images: the linear image, the nonlinear image and the image without sample. In order to validate our approach, we demonstrate this method for ZnSe at 532 nm where two-photon absorption is present and the nonlinear refractive index n2 is negative. The values of β (nonlinear absorption coefficient) and n2 we measured are very close to the values found in other literature.

  13. Semiconductor Laser Multi-Spectral Sensing and Imaging

    Directory of Open Access Journals (Sweden)

    Han Q. Le

    2010-01-01

    Full Text Available Multi-spectral laser imaging is a technique that can offer a combination of the laser capability of accurate spectral sensing with the desirable features of passive multispectral imaging. The technique can be used for detection, discrimination, and identification of objects by their spectral signature. This article describes and reviews the development and evaluation of semiconductor multi-spectral laser imaging systems. Although the method is certainly not specific to any laser technology, the use of semiconductor lasers is significant with respect to practicality and affordability. More relevantly, semiconductor lasers have their own characteristics; they offer excellent wavelength diversity but usually with modest power. Thus, system design and engineering issues are analyzed for approaches and trade-offs that can make the best use of semiconductor laser capabilities in multispectral imaging. A few systems were developed and the technique was tested and evaluated on a variety of natural and man-made objects. It was shown capable of high spectral resolution imaging which, unlike non-imaging point sensing, allows detecting and discriminating objects of interest even without a priori spectroscopic knowledge of the targets. Examples include material and chemical discrimination. It was also shown capable of dealing with the complexity of interpreting diffuse scattered spectral images and produced results that could otherwise be ambiguous with conventional imaging. Examples with glucose and spectral imaging of drug pills were discussed. Lastly, the technique was shown with conventional laser spectroscopy such as wavelength modulation spectroscopy to image a gas (CO. These results suggest the versatility and power of multi-spectral laser imaging, which can be practical with the use of semiconductor lasers.

  14. Multiplexed Spectral Imaging of 120 Different Fluorescent Labels.

    Directory of Open Access Journals (Sweden)

    Alex M Valm

    Full Text Available The number of fluorescent labels that can unambiguously be distinguished in a single image when acquired through band pass filters is severely limited by the spectral overlap of available fluorophores. The recent development of spectral microscopy and the application of linear unmixing algorithms to spectrally recorded image data have allowed simultaneous imaging of fluorophores with highly overlapping spectra. However, the number of distinguishable fluorophores is still limited by the unavoidable decrease in signal to noise ratio when fluorescence signals are fractionated over multiple wavelength bins. Here we present a spectral image analysis algorithm to greatly expand the number of distinguishable objects labeled with binary combinations of fluorophores. Our algorithm utilizes a priori knowledge about labeled specimens and imposes a binary label constraint on the unmixing solution. We have applied our labeling and analysis strategy to identify microbes labeled by fluorescence in situ hybridization and here demonstrate the ability to distinguish 120 differently labeled microbes in a single image.

  15. Adaptive nonlinear microscopy for whole tissue imaging

    Science.gov (United States)

    Müllenbroich, M. Caroline; McGhee, Ewan J.; Wright, Amanda J.; Anderson, Kurt I.; Mathieson, Keith

    2013-02-01

    Nonlinear microscopy is capable of imaging biological tissue non-invasively with sub-cellular resolution in three dimensions. For efficient multiphoton signal generation, it is necessary to focus high power, ultra-fast laser pulses into a volume of femtolitres. Aberrations introduced either by the system's optical setup or the sample under investigation cause a broadening of the diffraction limited focal spot which leads to loss of image intensity and resolution. Adaptive optics provides a means to compensate for these aberrations and is capable of restoring resolution and signal strength when imaging at depth. We describe the use of a micro-electro-mechanical systems (MEMS) deformable membrane mirror in a multiphoton adaptive microscope. The aberration correction is determined in a wavefront sensorless approach by rapidly altering the mirror shape with a random search algorithm until the fluorescence or second harmonic signal intensity is improved. We demonstrate the benefits of wavefront correction in a wide-variety of samples, including urea crystals, convallaria and organotypic tissue cultures. We show how the optimization algorithm can be adjusted, for example by including a bleaching compensation, to allow the user to switch between different imaging modalities, producing a versatile approach to aberration correction.

  16. Mapping the Physical Properties of Cosmic Hot Gas with Hyper-spectral Imaging

    CERN Document Server

    O'Dwyer, M; Raychaudhuri, S; Dwyer, Mark O'; Ponman, Trevor; Raychaudhury, Ela Claridge & Somak

    2005-01-01

    A novel inversion technique is proposed to compute parametric maps showing the temperature, density and chemical composition of cosmic hot gas from X-ray hyper-spectral images. The parameters are recovered by constructing a unique non-linear mapping derived by combining a physics-based modelling of the X-ray spectrum with the selection of optimal bandpass filters. Preliminary results and analysis are presented.

  17. Spectral Imaging Visualization and Tracking System Project

    Data.gov (United States)

    National Aeronautics and Space Administration — To address the NASA Earth Observation Mission need for innovative optical tracking systems, Physical Optics Corporation (POC) proposes to develop a new Spectral...

  18. Jacobi spectral collocation method for the approximate solution of multidimensional nonlinear Volterra integral equation.

    Science.gov (United States)

    Wei, Yunxia; Chen, Yanping; Shi, Xiulian; Zhang, Yuanyuan

    2016-01-01

    We present in this paper the convergence properties of Jacobi spectral collocation method when used to approximate the solution of multidimensional nonlinear Volterra integral equation. The solution is sufficiently smooth while the source function and the kernel function are smooth. We choose the Jacobi-Gauss points associated with the multidimensional Jacobi weight function [Formula: see text] (d denotes the space dimensions) as the collocation points. The error analysis in [Formula: see text]-norm and [Formula: see text]-norm theoretically justifies the exponential convergence of spectral collocation method in multidimensional space. We give two numerical examples in order to illustrate the validity of the proposed Jacobi spectral collocation method.

  19. Smoothing of Fused Spectral Consistent Satellite Images

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2006-01-01

    on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. (2005) proposed a method of fusion of satellite images that is based on the properties of imaging physics...

  20. Nonlinear Deep Kernel Learning for Image Annotation.

    Science.gov (United States)

    Jiu, Mingyuan; Sahbi, Hichem

    2017-02-08

    Multiple kernel learning (MKL) is a widely used technique for kernel design. Its principle consists in learning, for a given support vector classifier, the most suitable convex (or sparse) linear combination of standard elementary kernels. However, these combinations are shallow and often powerless to capture the actual similarity between highly semantic data, especially for challenging classification tasks such as image annotation. In this paper, we redefine multiple kernels using deep multi-layer networks. In this new contribution, a deep multiple kernel is recursively defined as a multi-layered combination of nonlinear activation functions, each one involves a combination of several elementary or intermediate kernels, and results into a positive semi-definite deep kernel. We propose four different frameworks in order to learn the weights of these networks: supervised, unsupervised, kernel-based semisupervised and Laplacian-based semi-supervised. When plugged into support vector machines (SVMs), the resulting deep kernel networks show clear gain, compared to several shallow kernels for the task of image annotation. Extensive experiments and analysis on the challenging ImageCLEF photo annotation benchmark, the COREL5k database and the Banana dataset validate the effectiveness of the proposed method.

  1. The quantile spectral density and comparison based tests for nonlinear time series

    CERN Document Server

    Lee, Junbum

    2011-01-01

    In this paper we consider tests for nonlinear time series, which are motivated by the notion of serial dependence. The proposed tests are based on comparisons with the quantile spectral density, which can be considered as a quantile version of the usual spectral density function. The quantile spectral density 'measures' sequential dependence structure of a time series, and is well defined under relatively weak mixing conditions. We propose an estimator for the quantile spectral density and derive its asympototic sampling properties. We use the quantile spectral density to construct a goodness of fit test for time series and explain how this test can also be used for comparing the sequential dependence structure of two time series. The method is illustrated with simulations and some real data examples.

  2. Invariant representation for spectral reflectance images and its application

    Directory of Open Access Journals (Sweden)

    Ibrahim Abdelhameed

    2011-01-01

    Full Text Available Abstract Spectral images as well as color images observed from object surfaces are much influenced by various illumination conditions such as shading and specular highlight. Several invariant representations were proposed for these conditions using the standard dichromatic reflection model of dielectric materials. However, these representations are inadequate for other materials like metal. This article proposes an invariant representation that is derived from the standard dichromatic reflection model for dielectric and the extended dichromatic reflection model for metal. We show that a normalized surface-spectral reflectance by the minimum reflectance is invariant to highlights, shading, surface geometry, and illumination intensity. Here the illumination spectrum and the spectral sensitivity functions of the imaging system are measured in a separate way. As an application of the proposed invariant representation, a segmentation algorithm based on the proposed representation is presented for effectively segmenting spectral images of natural scenes and bare circuit boards.

  3. Digital staining for histopathology multispectral images by the combined application of spectral enhancement and spectral transformation.

    Science.gov (United States)

    Bautista, Pinky A; Yagi, Yukako

    2011-01-01

    In this paper we introduced a digital staining method for histopathology images captured with an n-band multispectral camera. The method consisted of two major processes: enhancement of the original spectral transmittance and the transformation of the enhanced transmittance to its target spectral configuration. Enhancement is accomplished by shifting the original transmittance with the scaled difference between the original transmittance and the transmittance estimated with m dominant principal component (PC) vectors;the m-PC vectors were determined from the transmittance samples of the background image. Transformation of the enhanced transmittance to the target spectral configuration was done using an nxn transformation matrix, which was derived by applying a least square method to the enhanced and target spectral training data samples of the different tissue components. Experimental results on the digital conversion of a hematoxylin and eosin (H&E) stained multispectral image to its Masson's trichrome stained (MT) equivalent shows the viability of the method.

  4. Efficient Hybrid-Spectral Model for Fully Nonlinear Numerical Wave Tank

    DEFF Research Database (Denmark)

    Christiansen, Torben; Bingham, Harry B.; Engsig-Karup, Allan Peter;

    2013-01-01

    A new hybrid-spectral solution strategy is proposed for the simulation of the fully nonlinear free surface equations based on potential flow theory. A Fourier collocation method is adopted horisontally for the discretization of the free surface equations. This is combined with a modal Chebyshev T...

  5. Interpretation of archaeological small-scale features in spectral images

    DEFF Research Database (Denmark)

    Grøn, Ole; Palmer, Susanna; Stylegar, Frans-Arne;

    2011-01-01

    The paper's focus is the use of spectral images for the distinction of small archaeological anomalies on the basis of the authors work. Special attention is given to the ground-truthing perspective in the discussion of a number of cases from Norway. Different approaches to pattern-recognition are......-recognition are considered in the light of the increasing availability of hyper-spectral images that are difficult to analyse using visual inspection alone....

  6. Spectral mixture analysis of EELS spectrum-images

    OpenAIRE

    Dobigeon, Nicolas; Brun, Nathalie

    2012-01-01

    Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, Earth scientists try to recover the reflectance spectra of macroscopic materials (e.g., water, grass, mineral types...) present in an observed scene and to estimate their respective proportions in each mixed pixel of the acquired image. This task is usually referred to as spectral...

  7. Color Image Segmentation Method Based on Improved Spectral Clustering Algorithm

    OpenAIRE

    Dong Qin

    2014-01-01

    Contraposing to the features of image data with high sparsity of and the problems on determination of clustering numbers, we try to put forward an color image segmentation algorithm, combined with semi-supervised machine learning technology and spectral graph theory. By the research of related theories and methods of spectral clustering algorithms, we introduce information entropy conception to design a method which can automatically optimize the scale parameter value. So it avoids the unstab...

  8. Constrained optimization for image restoration using nonlinear programming

    Science.gov (United States)

    Yeh, C.-L.; Chin, R. T.

    1985-01-01

    The constrained optimization problem for image restoration, utilizing incomplete information and partial constraints, is formulated using nonlinear proramming techniques. This method restores a distorted image by optimizing a chosen object function subject to available constraints. The penalty function method of nonlinear programming is used. Both linear or nonlinear object function, and linear or nonlinear constraint functions can be incorporated in the formulation. This formulation provides a generalized approach to solve constrained optimization problems for image restoration. Experiments using this scheme have been performed. The results are compared with those obtained from other restoration methods and the comparative study is presented.

  9. A parametric estimation approach to instantaneous spectral imaging.

    Science.gov (United States)

    Oktem, Figen S; Kamalabadi, Farzad; Davila, Joseph M

    2014-12-01

    Spectral imaging, the simultaneous imaging and spectroscopy of a radiating scene, is a fundamental diagnostic technique in the physical sciences with widespread application. Due to the intrinsic limitation of two-dimensional (2D) detectors in capturing inherently three-dimensional (3D) data, spectral imaging techniques conventionally rely on a spatial or spectral scanning process, which renders them unsuitable for dynamic scenes. In this paper, we present a nonscanning (instantaneous) spectral imaging technique that estimates the physical parameters of interest by combining measurements with a parametric model and solving the resultant inverse problem computationally. The associated inverse problem, which can be viewed as a multiframe semiblind deblurring problem (with shift-variant blur), is formulated as a maximum a posteriori (MAP) estimation problem since in many such experiments prior statistical knowledge of the physical parameters can be well estimated. Subsequently, an efficient dynamic programming algorithm is developed to find the global optimum of the nonconvex MAP problem. Finally, the algorithm and the effectiveness of the spectral imaging technique are illustrated for an application in solar spectral imaging. Numerical simulation results indicate that the physical parameters can be estimated with the same order of accuracy as state-of-the-art slit spectroscopy but with the added benefit of an instantaneous, 2D field-of-view. This technique will be particularly useful for studying the spectra of dynamic scenes encountered in space remote sensing.

  10. The Sensitivity of Hybrid Differential Stereoscopy for Spectral Imaging

    CERN Document Server

    DeForest, Craig E

    2007-01-01

    Stereoscopic spectral imaging is an observing technique that affords rapid acquisition of limited spectral information over an entire image plane simultaneously. Light from a telescope is dispersed into multiple spectral orders, which are imaged separately, and two or more of the dispersed images are combined using an analogy between the (x,y,\\lambda) spectral data space and conventional (x,y,z) three-space. Because no photons are deliberately destroyed during image acquisition, the technique is much more photon-efficient in some observing regimes than existing techniques such as scanned-filtergraph or scanned-slit spectral imaging. Hybrid differential stereoscopy, which uses a combination of conventional cross-correlation stereoscopy and linear approximation theory to extract the central wavelength of a spectral line, has been used to produce solar Stokes-V (line-of-sight) magnetograms in the 617.34 nm Fe I line, and more sophisticated inversion techniques are currently being used to derive Doppler and line ...

  11. A conservative Fourier pseudo-spectral method for the nonlinear Schrödinger equation

    Science.gov (United States)

    Gong, Yuezheng; Wang, Qi; Wang, Yushun; Cai, Jiaxiang

    2017-01-01

    A Fourier pseudo-spectral method that conserves mass and energy is developed for a two-dimensional nonlinear Schrödinger equation. By establishing the equivalence between the semi-norm in the Fourier pseudo-spectral method and that in the finite difference method, we are able to extend the result in Ref. [56] to prove that the optimal rate of convergence of the new method is in the order of O (N-r +τ2) in the discrete L2 norm without any restrictions on the grid ratio, where N is the number of modes used in the spectral method and τ is the time step size. A fast solver is then applied to the discrete nonlinear equation system to speed up the numerical computation for the high order method. Numerical examples are presented to show the efficiency and accuracy of the new method.

  12. A Stabilised Nodal Spectral Element Method for Fully Nonlinear Water Waves

    CERN Document Server

    Engsig-Karup, Allan Peter; Bigoni, Daniele

    2015-01-01

    We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite element method proposed by Cai et al (1998) \\cite{CaiEtAl1998}, although the numerical implementation differs greatly. Features of the proposed spectral element method include: nodal Lagrange basis functions, a general quadrature-free approach and gradient recovery using global $L^2$ projections. The quartic nonlinear terms present in the Zakharov form of the free surface conditions can cause severe aliasing problems and consequently numerical instability for marginally resolved or very steep waves. We show how the scheme can be stabilised through a combination of over-integration of the Galerkin projections and a mild spectral filtering on a per element basis. This effectively removes any aliasing driven instabilities while retaining the high-order accuracy of the numerical...

  13. Image registration based on matrix perturbation analysis using spectral graph

    Institute of Scientific and Technical Information of China (English)

    Chengcai Leng; Zheng Tian; Jing Li; Mingtao Ding

    2009-01-01

    @@ We present a novel perspective on characterizing the spectral correspondence between nodes of the weighted graph with application to image registration.It is based on matrix perturbation analysis on the spectral graph.The contribution may be divided into three parts.Firstly, the perturbation matrix is obtained by perturbing the matrix of graph model.Secondly, an orthogonal matrix is obtained based on an optimal parameter, which can better capture correspondence features.Thirdly, the optimal matching matrix is proposed by adjusting signs of orthogonal matrix for image registration.Experiments on both synthetic images and real-world images demonstrate the effectiveness and accuracy of the proposed method.

  14. The influence of nonlinear effects on the spectral efficiency of multiinput antenna systems

    Directory of Open Access Journals (Sweden)

    Vishniakova J. V.

    2015-08-01

    Full Text Available The analysis technique and design algorithm are proposed for multiinput antenna systems, based on the mathematical model developed. The technique and algorithm described allow the analysis of a wide class of multiinput systems, in particular, MIMO systems, reconfigurable multiantenna systems, multiinput systems with nonlinear components and devices. The paper presents numerical analysis results of the intermodulation interference effect on the spectral efficiency of a multiinput system with nonlinear elements in receiving antennas, obtained using the methods, algorithms and software products developed. It is shown that in the nonlinear system intermodulation interferences appear, and the spectral efficiency of the data transmission system decays near the operating frequency due to the appearance of additional combinational components in the frequency response of the system. This effect depends on the degree of nonlinearity, radiated power, the level of interfering signals. Based on the results obtained, it was concluded that the presence of nonlinear elements and devices must be taken into account in the design and analysis processes of multiinput multiantenna systems, considering the specific types of those nonlinearities.

  15. Upconversion based spectral imaging in 6 to 8 μm spectral regime

    DEFF Research Database (Denmark)

    Junaid, Saher; Tidemand-Lichtenberg, Peter; Pedersen, Christian

    2017-01-01

    Spectral imaging in the 6 to 8μm range has great potential for medical diagnostics. Here a novel technique based on frequency upconversion of the infrared images to the near visible for subsequent acquisition using a Si-CCD camera is investigated. The upconversion unit consists of an AgGaS2 crystal...

  16. Hyper-spectral image segmentation using spectral clustering with covariance descriptors

    Science.gov (United States)

    Kursun, Olcay; Karabiber, Fethullah; Koc, Cemalettin; Bal, Abdullah

    2009-02-01

    Image segmentation is an important and difficult computer vision problem. Hyper-spectral images pose even more difficulty due to their high-dimensionality. Spectral clustering (SC) is a recently popular clustering/segmentation algorithm. In general, SC lifts the data to a high dimensional space, also known as the kernel trick, then derive eigenvectors in this new space, and finally using these new dimensions partition the data into clusters. We demonstrate that SC works efficiently when combined with covariance descriptors that can be used to assess pixelwise similarities rather than in the high-dimensional Euclidean space. We present the formulations and some preliminary results of the proposed hybrid image segmentation method for hyper-spectral images.

  17. Nonlinear images of scatterers in chirped pulsed laser beams

    Institute of Scientific and Technical Information of China (English)

    Hu Yong-Hua; Wang You-Wen; Wen Shuang-Chun; Fan Dian-Yuan

    2010-01-01

    The bandwidth and the duration of incident pulsed beam are proved to play important roles in modifying the nonlinear image of amplitude-type scatterer.It is found that the initially positive chirp-type bandwidth can suppress the nonlinear image,while the negative one can enhance it,and that both effects are inversely proportional to the incident pulse duration.Numerical simulations further demonstrate that the location of nonlinear image is at the conjugate plane of the scatterer and that,for negatively pre-chirped pulsed beam,the nonlinear image peak intensity can be higher than that in the corresponding monochromatic case under certain conditions.Moreover the effect of group velocity dispersion on nonlinear image is found to be similar to that of chirp-type bandwidth.

  18. Unsupervised texture image segmentation using multilayer data condensation spectral clustering

    Science.gov (United States)

    Liu, Hanqiang; Jiao, Licheng; Zhao, Feng

    2010-07-01

    A novel unsupervised texture image segmentation using a multilayer data condensation spectral clustering algorithm is presented. First, the texture features of each image pixel are extracted by the stationary wavelet transform and a multilayer data condensation method is performed on this texture features data set to obtain a condensation subset. Second, the spectral clustering algorithm based on the manifold similarity measure is used to cluster the condensation subset. Finally, according to the clustering result of the condensation subset, the nearest-neighbor method is adopted to obtain the original image-segmentation result. In the experiments, we apply our method to solve the texture and synthetic aperture radar image segmentation and take self-tuning k-nearest-neighbor spectral clustering and Nyström methods for baseline comparisons. The experimental results show that the proposed method is more robust and effective for texture image segmentation.

  19. Spectral image reconstruction by a tunable LED illumination

    Science.gov (United States)

    Lin, Meng-Chieh; Tsai, Chen-Wei; Tien, Chung-Hao

    2013-09-01

    Spectral reflectance estimation of an object via low-dimensional snapshot requires both image acquisition and a post numerical estimation analysis. In this study, we set up a system incorporating a homemade cluster of LEDs with spectral modulation for scene illumination, and a multi-channel CCD to acquire multichannel images by means of fully digital process. Principal component analysis (PCA) and pseudo inverse transformation were used to reconstruct the spectral reflectance in a constrained training set, such as Munsell and Macbeth Color Checker. The average reflectance spectral RMS error from 34 patches of a standard color checker were 0.234. The purpose is to investigate the use of system in conjunction with the imaging analysis for industry or medical inspection in a fast and acceptable accuracy, where the approach was preliminary validated.

  20. IMAGE RESTORATION: DESIGN OF NON-LINEAR FILTER (LR

    Directory of Open Access Journals (Sweden)

    Shenbagarajan Anantharajan

    2012-11-01

    Full Text Available In this proposed method, various types of noise models are subjected to an image and apply the nonlinear filter to reconstruct the original image from degraded image. Image restoration is a technique to attempt of reconstructs the original image by using a degraded phenomenon. In this paper the Lucy-Richardson filter is reconstruct the degraded image which closely resembles the original image. This paper deals with the various noise models and nonlinear filter. Objective of this paper is to study the various noise models and restoration filters in depth at restoration area.

  1. Multilayer Array Transducer for Nonlinear Ultrasound Imaging

    Science.gov (United States)

    Owen, Neil R.; Kaczkowski, Peter J.; Li, Tong; Gross, Dan; Postlewait, Steven M.; Curra, Francesco P.

    2011-09-01

    The properties of nonlinear acoustic wave propagation are known to be able to improve the resolution of ultrasound imaging, and could be used to dynamically estimate the physical properties of tissue. However, transducers capable of launching a wave that becomes nonlinear through propagation do not typically have the necessary bandwidth to detect the higher harmonics. Here we present the design and characterization of a novel multilayer transducer for high intensity transmit and broadband receive. The transmit layer was made from a narrow-band, high-power piezoceramic (PZT), with nominal frequency of 2.0 MHz, that was diced into an array of 32 elements. Each element was 0.300 mm wide and 6.3 mm in elevation, and with a pitch of 0.400 mm the overall aperture width was 12.7 mm. A quarter-wave matching layer was attached to the PZT substrate to improve transmit efficiency and bandwidth. The overlaid receive layer was made from polyvinylidene fluoride (PVDF) that had gold metalization on one side. A custom two-sided flex circuit routed electrical connections to the PZT elements and patterned the PVDF elements; the PZT and PVDF elements had identical apertures. A low viscosity and electrically nonconductive epoxy was used for all adhesion layers. Characterization of electrical parameters and acoustic output were performed per standard methods, where transmit and receive events were driven by a software-controlled ultrasound engine. Echo data, collected from ex vivo tissue and digitized at 45 MS/s, exhibited frequency content up to the 4th harmonic of the 2 MHz transmit frequency.

  2. Nonlinear optical microscopy for imaging thin films and surfaces

    Energy Technology Data Exchange (ETDEWEB)

    Smilowitz, L.B.; McBranch, D.W.; Robinson, J.M.

    1995-03-01

    We have used the inherent surface sensitivity of second harmonic generation to develop an instrument for nonlinear optical microscopy of surfaces and interfaces. We have demonstrated the use of several nonlinear optical responses for imaging thin films. The second harmonic response of a thin film of C{sub 60} has been used to image patterned films. Two photon absorption light induced fluorescence has been used to image patterned thin films of Rhodamine 6G. Applications of nonlinear optical microscopy include the imaging of charge injection and photoinduced charge transfer between layers in semiconductor heterojunction devices as well as across membranes in biological systems.

  3. Advances in Spectral-Spatial Classification of Hyperspectral Images

    Science.gov (United States)

    Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

    2012-01-01

    Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation and contrast of the spatial structures present in the image. Then the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines using the available spectral information and the extracted spatial information. Spatial post-processing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple classifier system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral-spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

  4. Hyperspectral image-based methods for spectral diversity

    Science.gov (United States)

    Sotomayor, Alejandro; Medina, Ollantay; Chinea, J. D.; Manian, Vidya

    2015-05-01

    Hyperspectral images are an important tool to assess ecosystem biodiversity. To obtain more precise analysis of biodiversity indicators that agree with indicators obtained using field data, analysis of spectral diversity calculated from images have to be validated with field based diversity estimates. The plant species richness is one of the most important indicators of biodiversity. This indicator can be measured in hyperspectral images considering the Spectral Variation Hypothesis (SVH) which states that the spectral heterogeneity is related to spatial heterogeneity and thus to species richness. The goal of this research is to capture spectral heterogeneity from hyperspectral images for a terrestrial neo tropical forest site using Vector Quantization (VQ) method and then use the result for prediction of plant species richness. The results are compared with that of Hierarchical Agglomerative Clustering (HAC). The validation of the process index is done calculating the Pearson correlation coefficient between the Shannon entropy from actual field data and the Shannon entropy computed in the images. One of the advantages of developing more accurate analysis tools would be the extension of the analysis to larger zones. Multispectral image with a lower spatial resolution has been evaluated as a prospective tool for spectral diversity.

  5. Multi-spectral confocal microendoscope for in-vivo imaging

    Science.gov (United States)

    Rouse, Andrew Robert

    The concept of in-vivo multi-spectral confocal microscopy is introduced. A slit-scanning multi-spectral confocal microendoscope (MCME) was built to demonstrate the technique. The MCME employs a flexible fiber-optic catheter coupled to a custom built slit-scan confocal microscope fitted with a custom built imaging spectrometer. The catheter consists of a fiber-optic imaging bundle linked to a miniature objective and focus assembly. The design and performance of the miniature objective and focus assembly are discussed. The 3mm diameter catheter may be used on its own or routed though the instrument channel of a commercial endoscope. The confocal nature of the system provides optical sectioning with 3mum lateral resolution and 30mum axial resolution. The prism based multi-spectral detection assembly is typically configured to collect 30 spectral samples over the visible chromatic range. The spectral sampling rate varies from 4nm/pixel at 490nm to 8nm/pixel at 660nm and the minimum resolvable wavelength difference varies from 7nm to 18nm over the same spectral range. Each of these characteristics are primarily dictated by the dispersive power of the prism. The MCME is designed to examine cellular structures during optical biopsy and to exploit the diagnostic information contained within the spectral domain. The primary applications for the system include diagnosis of disease in the gastro-intestinal tract and female reproductive system. Recent data from the grayscale imaging mode are presented. Preliminary multi-spectral results from phantoms, cell cultures, and excised human tissue are presented to demonstrate the potential of in-vivo multi-spectral imaging.

  6. Multi-spectral Image Analysis for Astaxanthin Coating Classification

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Nielsen, Michael Engelbrecht

    2011-01-01

    Industrial quality inspection using image analysis on astaxanthin coating in aquaculture feed pellets is of great importance for automatic production control. In this study multi-spectral image analysis of pellets was performed using LDA, QDA, SNV and PCA on pixel level and mean value of pixels...

  7. Image segmentation combining non-linear diffusion and the Nystrom extension

    Science.gov (United States)

    Izquierdo, Ebroul

    2005-07-01

    An approach for image segmentation is presented. Images are first preprocessed using multiscale simplification by nonlinear diffusion. Subsequently image segmentation of the resulting smoothed images is carried out. The actual segmentation step is based on the estimation of the Eigenvectors and Eigenvalues of a matrix derived from both the total dissimilarity and the total similarity between different groups of pixels in the image. This algorithm belong to the class of spectral methods, specifically, the Nystron extension introduced by Fowlkes et al in [1]. Stability analysis of the approximation of the underlying spectral partitioning is presented. Modifications of Fowlkes technique are proposed to improve the stability of the algorithm. The proposed modifications include a criterion for the selection of the initial sample and numerically stable estimations of ill-posed inverse matrices for the solution of the underlying mathematical problem. Results of selected computer experiments are reported to validate the superiority of the proposed approach when compared with the technique proposed in [1].

  8. Enhanced nonlinear spectral compression in fiber by external sinusoidal phase modulation

    Science.gov (United States)

    Boscolo, S.; Mouradian, L. Kh; Finot, C.

    2016-10-01

    We propose a new, simple approach to enhance the spectral compression process arising from nonlinear pulse propagation in an optical fiber. We numerically show that an additional sinusoidal temporal phase modulation of the pulse enables efficient reduction of the intensity level of the side lobes in the spectrum that are produced by the mismatch between the initial linear negative chirp of the pulse and the self-phase modulation-induced nonlinear positive chirp. Remarkable increase of both the extent of spectrum narrowing and the quality of the compressed spectrum is afforded by the proposed approach across a wide range of experimentally accessible parameters.

  9. Online unmixing of multitemporal hyperspectral images accounting for spectral variability

    CERN Document Server

    Thouvenin, Pierre-Antoine; Tourneret, Jean-Yves

    2015-01-01

    Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing an hyperspectral image -- referred to as endmembers -- and their relative abundance fractions in each pixel. In practice, the identified signatures may vary spectrally from an image to another due to varying acquisition conditions inducing possibly significant estimation errors. Against this background, hyperspectral unmixing of several images acquired over the same area is of considerable interest. Indeed, such an analysis enables the endmembers of the scene to be tracked and the corresponding endmember variability to be characterized. Sequential endmember estimation from a set of hyperspectral images is expected to provide improved performance when compared to methods analyzing the images independently. However, the significant size of hyperspectral data precludes the use of batch procedures to jointly estimate the mixture parameters of a sequence of hyperspectral images. Provided that each elementary component is pre...

  10. Probability of correct reconstruction in compressive spectral imaging

    Directory of Open Access Journals (Sweden)

    Samuel Eduardo Pinilla

    2016-08-01

    Full Text Available Coded Aperture Snapshot Spectral Imaging (CASSI systems capture the 3-dimensional (3D spatio-spectral information of a scene using a set of 2-dimensional (2D random coded Focal Plane Array (FPA measurements. A compressed sensing reconstruction algorithm is then used to recover the underlying spatio-spectral 3D data cube. The quality of the reconstructed spectral images depends exclusively on the CASSI sensing matrix, which is determined by the statistical structure of the coded apertures. The Restricted Isometry Property (RIP of the CASSI sensing matrix is used to determine the probability of correct image reconstruction and provides guidelines for the minimum number of FPA measurement shots needed for image reconstruction. Further, the RIP can be used to determine the optimal structure of the coded projections in CASSI. This article describes the CASSI optical architecture and develops the RIP for the sensing matrix in this system. Simulations show the higher quality of spectral image reconstructions when the RIP property is satisfied. Simulations also illustrate the higher performance of the optimal structured projections in CASSI.

  11. Spectral mixture analysis of EELS spectrum-images

    Energy Technology Data Exchange (ETDEWEB)

    Dobigeon, Nicolas [University of Toulouse, IRIT/INP-ENSEEIHT, 2 rue Camichel, 31071 Toulouse Cedex 7 (France); Brun, Nathalie, E-mail: nathalie.brun@u-psud.fr [University of Paris Sud, Laboratoire de Physique des Solides, CNRS, UMR 8502, 91405 Orsay Cedex (France)

    2012-09-15

    Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, Earth scientists try to recover the reflectance spectra of macroscopic materials (e.g., water, grass, mineral types Horizontal-Ellipsis ) present in an observed scene and to estimate their respective proportions in each mixed pixel of the acquired image. This task is usually referred to as spectral mixture analysis or spectral unmixing (SU). SU aims at decomposing the measured pixel spectrum into a collection of constituent spectra, called endmembers, and a set of corresponding fractions (abundances) that indicate the proportion of each endmember present in the pixel. Similarly, when processing spectrum-images, microscopists usually try to map elemental, physical and chemical state information of a given material. This paper reports how a SU algorithm dedicated to remote sensing hyperspectral images can be successfully applied to analyze spectrum-image resulting from electron energy-loss spectroscopy (EELS). SU generally overcomes standard limitations inherent to other multivariate statistical analysis methods, such as principal component analysis (PCA) or independent component analysis (ICA), that have been previously used to analyze EELS maps. Indeed, ICA and PCA may perform poorly for linear spectral mixture analysis due to the strong dependence between the abundances of the different materials. One example is presented here to demonstrate the potential of this technique for EELS analysis. -- Highlights: Black-Right-Pointing-Pointer EELS spectrum images are identical to hyperspectral images for Earth science. Black-Right-Pointing-Pointer Spectral unmixing algorithms have proliferated in the remote sensing field. Black-Right-Pointing-Pointer These powerful techniques can be successfully applied to EELS mapping. Black-Right-Pointing-Pointer Potential

  12. A New Spectral Local Linearization Method for Nonlinear Boundary Layer Flow Problems

    Directory of Open Access Journals (Sweden)

    S. S. Motsa

    2013-01-01

    Full Text Available We propose a simple and efficient method for solving highly nonlinear systems of boundary layer flow problems with exponentially decaying profiles. The algorithm of the proposed method is based on an innovative idea of linearizing and decoupling the governing systems of equations and reducing them into a sequence of subsystems of differential equations which are solved using spectral collocation methods. The applicability of the proposed method, hereinafter referred to as the spectral local linearization method (SLLM, is tested on some well-known boundary layer flow equations. The numerical results presented in this investigation indicate that the proposed method, despite being easy to develop and numerically implement, is very robust in that it converges rapidly to yield accurate results and is more efficient in solving very large systems of nonlinear boundary value problems of the similarity variable boundary layer type. The accuracy and numerical stability of the SLLM can further be improved by using successive overrelaxation techniques.

  13. Simulated annealing spectral clustering algorithm for image segmentation

    Institute of Scientific and Technical Information of China (English)

    Yifang Yang; and Yuping Wang

    2014-01-01

    The similarity measure is crucial to the performance of spectral clustering. The Gaussian kernel function based on the Euclidean distance is usual y adopted as the similarity mea-sure. However, the Euclidean distance measure cannot ful y reveal the complex distribution data, and the result of spectral clustering is very sensitive to the scaling parameter. To solve these problems, a new manifold distance measure and a novel simulated anneal-ing spectral clustering (SASC) algorithm based on the manifold distance measure are proposed. The simulated annealing based on genetic algorithm (SAGA), characterized by its rapid conver-gence to the global optimum, is used to cluster the sample points in the spectral mapping space. The proposed algorithm can not only reflect local and global consistency better, but also reduce the sensitivity of spectral clustering to the kernel parameter, which improves the algorithm’s clustering performance. To efficiently ap-ply the algorithm to image segmentation, the Nystr¨om method is used to reduce the computation complexity. Experimental re-sults show that compared with traditional clustering algorithms and those popular spectral clustering algorithms, the proposed algorithm can achieve better clustering performances on several synthetic datasets, texture images and real images.

  14. Imaging Cellular Dynamics with Spectral Relaxation Imaging Microscopy: Distinct Spectral Dynamics in Golgi Membranes of Living Cells

    Science.gov (United States)

    Lajevardipour, Alireza; Chon, James W. M.; Chattopadhyay, Amitabha; Clayton, Andrew H. A.

    2016-11-01

    Spectral relaxation from fluorescent probes is a useful technique for determining the dynamics of condensed phases. To this end, we have developed a method based on wide-field spectral fluorescence lifetime imaging microscopy to extract spectral relaxation correlation times of fluorescent probes in living cells. We show that measurement of the phase and modulation of fluorescence from two wavelengths permit the identification and determination of excited state lifetimes and spectral relaxation correlation times at a single modulation frequency. For NBD fluorescence in glycerol/water mixtures, the spectral relaxation correlation time determined by our approach exhibited good agreement with published dielectric relaxation measurements. We applied this method to determine the spectral relaxation dynamics in membranes of living cells. Measurements of the Golgi-specific C6-NBD-ceramide probe in living HeLa cells revealed sub-nanosecond spectral dynamics in the intracellular Golgi membrane and slower nanosecond spectral dynamics in the extracellular plasma membrane. We interpret the distinct spectral dynamics as a result of structural plasticity of the Golgi membrane relative to more rigid plasma membranes. To the best of our knowledge, these results constitute one of the first measurements of Golgi rotational dynamics.

  15. Imaging Cellular Dynamics with Spectral Relaxation Imaging Microscopy: Distinct Spectral Dynamics in Golgi Membranes of Living Cells.

    Science.gov (United States)

    Lajevardipour, Alireza; Chon, James W M; Chattopadhyay, Amitabha; Clayton, Andrew H A

    2016-11-22

    Spectral relaxation from fluorescent probes is a useful technique for determining the dynamics of condensed phases. To this end, we have developed a method based on wide-field spectral fluorescence lifetime imaging microscopy to extract spectral relaxation correlation times of fluorescent probes in living cells. We show that measurement of the phase and modulation of fluorescence from two wavelengths permit the identification and determination of excited state lifetimes and spectral relaxation correlation times at a single modulation frequency. For NBD fluorescence in glycerol/water mixtures, the spectral relaxation correlation time determined by our approach exhibited good agreement with published dielectric relaxation measurements. We applied this method to determine the spectral relaxation dynamics in membranes of living cells. Measurements of the Golgi-specific C6-NBD-ceramide probe in living HeLa cells revealed sub-nanosecond spectral dynamics in the intracellular Golgi membrane and slower nanosecond spectral dynamics in the extracellular plasma membrane. We interpret the distinct spectral dynamics as a result of structural plasticity of the Golgi membrane relative to more rigid plasma membranes. To the best of our knowledge, these results constitute one of the first measurements of Golgi rotational dynamics.

  16. PHISHING WEB IMAGE SEGMENTATION BASED ON IMPROVING SPECTRAL CLUSTERING

    Institute of Scientific and Technical Information of China (English)

    Li Yuancheng; Zhao Liujun; Jiao Runhai

    2011-01-01

    Abstract This paper proposes a novel phishing web image segmentation algorithm which based on improving spectral clustering.Firstly,we construct a set of points which are composed of spatial location pixels and gray levels from a given image.Secondly,the data is clustered in spectral space of the similar matrix of the set points,in order to avoid the drawbacks of K-means algorithm in the conventional spectral clustering method that is sensitive to initial clustering centroids and convergence to local optimal solution,we introduce the clone operator,Cauthy mutation to enlarge the scale of clustering centers,quantum-inspired evolutionary algorithm to find the global optimal clustering centroids.Compared with phishing web image segmentation based on K-means,experimental results show that the segmentation performance of our method gains much improvement.Moreover,our method can convergence to global optimal solution and is better in accuracy of phishing web segmentation.

  17. Test and analysis of spectral response for UV image intensifier

    Science.gov (United States)

    Qian, Yunsheng; Liu, Jian; Feng, Cheng; Lv, Yang; Zhang, Yijun

    2015-10-01

    The UV image intensifier is one kind of electric vacuum imaging device based on principle of photoelectronic imaging. To achieve solar-blind detection, its spectral response characteristic is extremely desirable. A broad spectrum response measurement system is developed. This instrument uses EQ-99 laser-driven light source to get broad spectrum in the range of 200 nm to 1700 nm. A special preamplifier as well as a test software is work out. The spectral response of the image intensifier can be tested in the range of 200~1700 nm. Using this spectrum response measuring instrument, the UV image intensifiers are tested. The spectral response at the spectral range of 200 nm to 600 nm are obtained. Because of the quantum efficiency of Te-Cs photocathode used in image intens ifier above 280nm wavelength still exists, especially at 280 nm to 320nm.Therefore, high-performance UV filters is required for solar blind UV detection. Based on two sets of UV filters, the influence of solar radiation on solar blind detection is calculated and analyzed.

  18. Face recognition with multi-resolution spectral feature images.

    Directory of Open Access Journals (Sweden)

    Zhan-Li Sun

    Full Text Available The one-sample-per-person problem has become an active research topic for face recognition in recent years because of its challenges and significance for real-world applications. However, achieving relatively higher recognition accuracy is still a difficult problem due to, usually, too few training samples being available and variations of illumination and expression. To alleviate the negative effects caused by these unfavorable factors, in this paper we propose a more accurate spectral feature image-based 2DLDA (two-dimensional linear discriminant analysis ensemble algorithm for face recognition, with one sample image per person. In our algorithm, multi-resolution spectral feature images are constructed to represent the face images; this can greatly enlarge the training set. The proposed method is inspired by our finding that, among these spectral feature images, features extracted from some orientations and scales using 2DLDA are not sensitive to variations of illumination and expression. In order to maintain the positive characteristics of these filters and to make correct category assignments, the strategy of classifier committee learning (CCL is designed to combine the results obtained from different spectral feature images. Using the above strategies, the negative effects caused by those unfavorable factors can be alleviated efficiently in face recognition. Experimental results on the standard databases demonstrate the feasibility and efficiency of the proposed method.

  19. Face recognition with multi-resolution spectral feature images.

    Science.gov (United States)

    Sun, Zhan-Li; Lam, Kin-Man; Dong, Zhao-Yang; Wang, Han; Gao, Qing-Wei; Zheng, Chun-Hou

    2013-01-01

    The one-sample-per-person problem has become an active research topic for face recognition in recent years because of its challenges and significance for real-world applications. However, achieving relatively higher recognition accuracy is still a difficult problem due to, usually, too few training samples being available and variations of illumination and expression. To alleviate the negative effects caused by these unfavorable factors, in this paper we propose a more accurate spectral feature image-based 2DLDA (two-dimensional linear discriminant analysis) ensemble algorithm for face recognition, with one sample image per person. In our algorithm, multi-resolution spectral feature images are constructed to represent the face images; this can greatly enlarge the training set. The proposed method is inspired by our finding that, among these spectral feature images, features extracted from some orientations and scales using 2DLDA are not sensitive to variations of illumination and expression. In order to maintain the positive characteristics of these filters and to make correct category assignments, the strategy of classifier committee learning (CCL) is designed to combine the results obtained from different spectral feature images. Using the above strategies, the negative effects caused by those unfavorable factors can be alleviated efficiently in face recognition. Experimental results on the standard databases demonstrate the feasibility and efficiency of the proposed method.

  20. Advances in Spectral-Spatial Classification of Hyperspectral Images

    Science.gov (United States)

    Fauvel, Mathieu; Tarabalka, Yuliya; Benediktsson, Jon Atli; Chanussot, Jocelyn; Tilton, James C.

    2012-01-01

    Recent advances in spectral-spatial classification of hyperspectral images are presented in this paper. Several techniques are investigated for combining both spatial and spectral information. Spatial information is extracted at the object (set of pixels) level rather than at the conventional pixel level. Mathematical morphology is first used to derive the morphological profile of the image, which includes characteristics about the size, orientation, and contrast of the spatial structures present in the image. Then, the morphological neighborhood is defined and used to derive additional features for classification. Classification is performed with support vector machines (SVMs) using the available spectral information and the extracted spatial information. Spatial postprocessing is next investigated to build more homogeneous and spatially consistent thematic maps. To that end, three presegmentation techniques are applied to define regions that are used to regularize the preliminary pixel-wise thematic map. Finally, a multiple-classifier (MC) system is defined to produce relevant markers that are exploited to segment the hyperspectral image with the minimum spanning forest algorithm. Experimental results conducted on three real hyperspectral images with different spatial and spectral resolutions and corresponding to various contexts are presented. They highlight the importance of spectral–spatial strategies for the accurate classification of hyperspectral images and validate the proposed methods.

  1. Optimal material discrimination using spectral x-ray imaging.

    Science.gov (United States)

    Nik, S J; Meyer, J; Watts, R

    2011-09-21

    Spectral x-ray imaging using novel photon counting x-ray detectors (PCDs) with energy resolving abilities is capable of providing energy-selective images. PCDs have energy thresholds, enabling the classification of photons into multiple energy bins. The extra energy information provided may allow materials such as iodine and calcium, or water and fat to be distinguishable. The information content of spectral x-ray images, however, depends on how the photons are grouped together. In this work, we present a model to optimize energy windows for maximum material discrimination. Multivariate statistics allows the confidence region of the correlated uncertainties to be mapped in the thickness space. Minimization of the uncertainties enables optimization of energy windows. Applications related to small animal imaging and breast imaging are considered.

  2. An Inverse Power Method for Nonlinear Eigenproblems with Applications in 1-Spectral Clustering and Sparse PCA

    CERN Document Server

    Hein, Matthias

    2010-01-01

    Many problems in machine learning and statistics can be formulated as (generalized) eigenproblems. In terms of the associated optimization problem, computing linear eigenvectors amounts to finding critical points of a quadratic function subject to quadratic constraints. In this paper we show that a certain class of constrained optimization problems with nonquadratic objective and constraints can be understood as nonlinear eigenproblems. We derive a generalization of the inverse power method which is guaranteed to converge to a nonlinear eigenvector. We apply the inverse power method to 1-spectral clustering and sparse PCA which can naturally be formulated as nonlinear eigenproblems. In both applications we achieve state-of-the-art results in terms of solution quality and runtime. Moving beyond the standard eigenproblem should be useful also in many other applications and our inverse power method can be easily adapted to new problems.

  3. A Bivariate Chebyshev Spectral Collocation Quasilinearization Method for Nonlinear Evolution Parabolic Equations

    Directory of Open Access Journals (Sweden)

    S. S. Motsa

    2014-01-01

    Full Text Available This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs. The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.

  4. A bivariate Chebyshev spectral collocation quasilinearization method for nonlinear evolution parabolic equations.

    Science.gov (United States)

    Motsa, S S; Magagula, V M; Sibanda, P

    2014-01-01

    This paper presents a new method for solving higher order nonlinear evolution partial differential equations (NPDEs). The method combines quasilinearisation, the Chebyshev spectral collocation method, and bivariate Lagrange interpolation. In this paper, we use the method to solve several nonlinear evolution equations, such as the modified KdV-Burgers equation, highly nonlinear modified KdV equation, Fisher's equation, Burgers-Fisher equation, Burgers-Huxley equation, and the Fitzhugh-Nagumo equation. The results are compared with known exact analytical solutions from literature to confirm accuracy, convergence, and effectiveness of the method. There is congruence between the numerical results and the exact solutions to a high order of accuracy. Tables were generated to present the order of accuracy of the method; convergence graphs to verify convergence of the method and error graphs are presented to show the excellent agreement between the results from this study and the known results from literature.

  5. Automated spectral imaging for clinical diagnostics

    Science.gov (United States)

    Breneman, John; Heffelfinger, David M.; Pettipiece, Ken; Tsai, Chris; Eden, Peter; Greene, Richard A.; Sorensen, Karen J.; Stubblebine, Will; Witney, Frank

    1998-04-01

    Bio-Rad Laboratories supplies imaging equipment for many applications in the life sciences. As part of our effort to offer more flexibility to the investigator, we are developing a microscope-based imaging spectrometer for the automated detection and analysis of either conventionally or fluorescently labeled samples. Immediate applications will include the use of fluorescence in situ hybridization (FISH) technology. The field of cytogenetics has benefited greatly from the increased sensitivity of FISH producing simplified analysis of complex chromosomal rearrangements. FISH methods for identification lends itself to automation more easily than the current cytogenetics industry standard of G- banding, however, the methods are complementary. Several technologies have been demonstrated successfully for analyzing the signals from labeled samples, including filter exchanging and interferometry. The detection system lends itself to other fluorescent applications including the display of labeled tissue sections, DNA chips, capillary electrophoresis or any other system using color as an event marker. Enhanced displays of conventionally stained specimens will also be possible.

  6. Toward a Broadband Astro-comb: Effects of Nonlinear Spectral Broadening in Optical Fibers

    CERN Document Server

    Chang, Guoqing; Phillips, David F; Walsworth, Ronald L; Kärtner, Franz X

    2010-01-01

    We propose and analyze a new approach to generate a broadband astro-comb by spectral broadening of a narrowband astro-comb inside a highly nonlinear optical fiber. Numerical modeling shows that cascaded four-wave-mixing dramatically degrades the input comb's side-mode suppression and causes side-mode amplitude asymmetry. These two detrimental effects can systematically shift the center-of-gravity of astro-comb spectral lines as measured by an astrophysical spectrograph with resolution \\approx100,000; and thus lead to wavelength calibration inaccuracy and instability. Our simulations indicate that this performance penalty, as a result of nonlinear spectral broadening, can be compensated by using a filtering cavity configured for double-pass. As an explicit example, we present a design based on an Yb-fiber source comb (with 1 GHz repetition rate) that is filtered by double-passing through a low finesse cavity (finesse = 208), and subsequent spectrally broadened in a 2-cm, SF6-glass photonic crystal fiber. Spann...

  7. Single shot, double differential spectral measurements of inverse Compton scattering in the nonlinear regime

    Directory of Open Access Journals (Sweden)

    Y. Sakai

    2017-06-01

    Full Text Available Inverse Compton scattering (ICS is a unique mechanism for producing fast pulses—picosecond and below—of bright photons, ranging from x to γ rays. These nominally narrow spectral bandwidth electromagnetic radiation pulses are efficiently produced in the interaction between intense, well-focused electron and laser beams. The spectral characteristics of such sources are affected by many experimental parameters, with intense laser effects often dominant. A laser field capable of inducing relativistic oscillatory motion may give rise to harmonic generation and, importantly for the present work, nonlinear redshifting, both of which dilute the spectral brightness of the radiation. As the applications enabled by this source often depend sensitively on its spectra, it is critical to resolve the details of the wavelength and angular distribution obtained from ICS collisions. With this motivation, we present an experimental study that greatly improves on previous spectral measurement methods based on x-ray K-edge filters, by implementing a multilayer bent-crystal x-ray spectrometer. In tandem with a collimating slit, this method reveals a projection of the double differential angular-wavelength spectrum of the ICS radiation in a single shot. The measurements enabled by this diagnostic illustrate the combined off-axis and nonlinear-field-induced redshifting in the ICS emission process. The spectra obtained illustrate in detail the strength of the normalized laser vector potential, and provide a nondestructive measure of the temporal and spatial electron-laser beam overlap.

  8. Single shot, double differential spectral measurements of inverse Compton scattering in the nonlinear regime

    Science.gov (United States)

    Sakai, Y.; Gadjev, I.; Hoang, P.; Majernik, N.; Nause, A.; Fukasawa, A.; Williams, O.; Fedurin, M.; Malone, B.; Swinson, C.; Kusche, K.; Polyanskiy, M.; Babzien, M.; Montemagno, M.; Zhong, Z.; Siddons, P.; Pogorelsky, I.; Yakimenko, V.; Kumita, T.; Kamiya, Y.; Rosenzweig, J. B.

    2017-06-01

    Inverse Compton scattering (ICS) is a unique mechanism for producing fast pulses—picosecond and below—of bright photons, ranging from x to γ rays. These nominally narrow spectral bandwidth electromagnetic radiation pulses are efficiently produced in the interaction between intense, well-focused electron and laser beams. The spectral characteristics of such sources are affected by many experimental parameters, with intense laser effects often dominant. A laser field capable of inducing relativistic oscillatory motion may give rise to harmonic generation and, importantly for the present work, nonlinear redshifting, both of which dilute the spectral brightness of the radiation. As the applications enabled by this source often depend sensitively on its spectra, it is critical to resolve the details of the wavelength and angular distribution obtained from ICS collisions. With this motivation, we present an experimental study that greatly improves on previous spectral measurement methods based on x-ray K -edge filters, by implementing a multilayer bent-crystal x-ray spectrometer. In tandem with a collimating slit, this method reveals a projection of the double differential angular-wavelength spectrum of the ICS radiation in a single shot. The measurements enabled by this diagnostic illustrate the combined off-axis and nonlinear-field-induced redshifting in the ICS emission process. The spectra obtained illustrate in detail the strength of the normalized laser vector potential, and provide a nondestructive measure of the temporal and spatial electron-laser beam overlap.

  9. Spectral mixture analysis of EELS spectrum-images.

    Science.gov (United States)

    Dobigeon, Nicolas; Brun, Nathalie

    2012-09-01

    Recent advances in detectors and computer science have enabled the acquisition and the processing of multidimensional datasets, in particular in the field of spectral imaging. Benefiting from these new developments, Earth scientists try to recover the reflectance spectra of macroscopic materials (e.g., water, grass, mineral types…) present in an observed scene and to estimate their respective proportions in each mixed pixel of the acquired image. This task is usually referred to as spectral mixture analysis or spectral unmixing (SU). SU aims at decomposing the measured pixel spectrum into a collection of constituent spectra, called endmembers, and a set of corresponding fractions (abundances) that indicate the proportion of each endmember present in the pixel. Similarly, when processing spectrum-images, microscopists usually try to map elemental, physical and chemical state information of a given material. This paper reports how a SU algorithm dedicated to remote sensing hyperspectral images can be successfully applied to analyze spectrum-image resulting from electron energy-loss spectroscopy (EELS). SU generally overcomes standard limitations inherent to other multivariate statistical analysis methods, such as principal component analysis (PCA) or independent component analysis (ICA), that have been previously used to analyze EELS maps. Indeed, ICA and PCA may perform poorly for linear spectral mixture analysis due to the strong dependence between the abundances of the different materials. One example is presented here to demonstrate the potential of this technique for EELS analysis. Copyright © 2012 Elsevier B.V. All rights reserved.

  10. Biologically-inspired data decorrelation for hyper-spectral imaging

    Directory of Open Access Journals (Sweden)

    Ghita Ovidiu

    2011-01-01

    Full Text Available Abstract Hyper-spectral data allows the construction of more robust statistical models to sample the material properties than the standard tri-chromatic color representation. However, because of the large dimensionality and complexity of the hyper-spectral data, the extraction of robust features (image descriptors is not a trivial issue. Thus, to facilitate efficient feature extraction, decorrelation techniques are commonly applied to reduce the dimensionality of the hyper-spectral data with the aim of generating compact and highly discriminative image descriptors. Current methodologies for data decorrelation such as principal component analysis (PCA, linear discriminant analysis (LDA, wavelet decomposition (WD, or band selection methods require complex and subjective training procedures and in addition the compressed spectral information is not directly related to the physical (spectral characteristics associated with the analyzed materials. The major objective of this article is to introduce and evaluate a new data decorrelation methodology using an approach that closely emulates the human vision. The proposed data decorrelation scheme has been employed to optimally minimize the amount of redundant information contained in the highly correlated hyper-spectral bands and has been comprehensively evaluated in the context of non-ferrous material classification

  11. Systems and methods for selective detection and imaging in coherent Raman microscopy by spectral excitation shaping

    Science.gov (United States)

    Xie, Xiaoliang Sunney; Freudiger, Christian; Min, Wei

    2016-03-15

    A microscopy imaging system is disclosed that includes a light source system, a spectral shaper, a modulator system, an optics system, an optical detector and a processor. The light source system is for providing a first train of pulses and a second train of pulses. The spectral shaper is for spectrally modifying an optical property of at least some frequency components of the broadband range of frequency components such that the broadband range of frequency components is shaped producing a shaped first train of pulses to specifically probe a spectral feature of interest from a sample, and to reduce information from features that are not of interest from the sample. The modulator system is for modulating a property of at least one of the shaped first train of pulses and the second train of pulses at a modulation frequency. The optical detector is for detecting an integrated intensity of substantially all optical frequency components of a train of pulses of interest transmitted or reflected through the common focal volume. The processor is for detecting a modulation at the modulation frequency of the integrated intensity of substantially all of the optical frequency components of the train of pulses of interest due to the non-linear interaction of the shaped first train of pulses with the second train of pulses as modulated in the common focal volume, and for providing an output signal for a pixel of an image for the microscopy imaging system.

  12. Spectral imaging for contamination detection in food

    DEFF Research Database (Denmark)

    Carstensen, Jens Michael

    application of the technique is finding anomalies I supposedly homogeneous matter or homogeneous mixtures. This application occurs frequently in the food industry when different types of contamination are to be detected. Contaminants could be e.g. foreign matter, process-induced toxins, and microbiological...... spoilage. Many of these contaminants may be detected in the wavelength range visible to normal silicium-based camera sensors i.e. 350-1050 nm with proper care during sample preparation, sample presentation, image acquisition and analysis. This presentation will give an introduction to the techniques behind...

  13. Sparse electromagnetic imaging using nonlinear iterative shrinkage thresholding

    KAUST Repository

    Desmal, Abdulla

    2015-04-13

    A sparse nonlinear electromagnetic imaging scheme is proposed for reconstructing dielectric contrast of investigation domains from measured fields. The proposed approach constructs the optimization problem by introducing the sparsity constraint to the data misfit between the scattered fields expressed as a nonlinear function of the contrast and the measured fields and solves it using the nonlinear iterative shrinkage thresholding algorithm. The thresholding is applied to the result of every nonlinear Landweber iteration to enforce the sparsity constraint. Numerical results demonstrate the accuracy and efficiency of the proposed method in reconstructing sparse dielectric profiles.

  14. Spectral prior image constrained compressed sensing (spectral PICCS) for photon-counting computed tomography

    Science.gov (United States)

    Yu, Zhicong; Leng, Shuai; Li, Zhoubo; McCollough, Cynthia H.

    2016-09-01

    Photon-counting computed tomography (PCCT) is an emerging imaging technique that enables multi-energy imaging with only a single scan acquisition. To enable multi-energy imaging, the detected photons corresponding to the full x-ray spectrum are divided into several subgroups of bin data that correspond to narrower energy windows. Consequently, noise in each energy bin increases compared to the full-spectrum data. This work proposes an iterative reconstruction algorithm for noise suppression in the narrower energy bins used in PCCT imaging. The algorithm is based on the framework of prior image constrained compressed sensing (PICCS) and is called spectral PICCS; it uses the full-spectrum image reconstructed using conventional filtered back-projection as the prior image. The spectral PICCS algorithm is implemented using a constrained optimization scheme with adaptive iterative step sizes such that only two tuning parameters are required in most cases. The algorithm was first evaluated using computer simulations, and then validated by both physical phantoms and in vivo swine studies using a research PCCT system. Results from both computer-simulation and experimental studies showed substantial image noise reduction in narrow energy bins (43-73%) without sacrificing CT number accuracy or spatial resolution.

  15. SPARSE ELECTROMAGNETIC IMAGING USING NONLINEAR LANDWEBER ITERATIONS

    KAUST Repository

    Desmal, Abdulla

    2015-07-29

    A scheme for efficiently solving the nonlinear electromagnetic inverse scattering problem on sparse investigation domains is described. The proposed scheme reconstructs the (complex) dielectric permittivity of an investigation domain from fields measured away from the domain itself. Least-squares data misfit between the computed scattered fields, which are expressed as a nonlinear function of the permittivity, and the measured fields is constrained by the L0/L1-norm of the solution. The resulting minimization problem is solved using nonlinear Landweber iterations, where at each iteration a thresholding function is applied to enforce the sparseness-promoting L0/L1-norm constraint. The thresholded nonlinear Landweber iterations are applied to several two-dimensional problems, where the ``measured\\'\\' fields are synthetically generated or obtained from actual experiments. These numerical experiments demonstrate the accuracy, efficiency, and applicability of the proposed scheme in reconstructing sparse profiles with high permittivity values.

  16. Nonlinear plasmonic imaging techniques and their biological applications

    Science.gov (United States)

    Deka, Gitanjal; Sun, Chi-Kuang; Fujita, Katsumasa; Chu, Shi-Wei

    2017-01-01

    Nonlinear optics, when combined with microscopy, is known to provide advantages including novel contrast, deep tissue observation, and minimal invasiveness. In addition, special nonlinearities, such as switch on/off and saturation, can enhance the spatial resolution below the diffraction limit, revolutionizing the field of optical microscopy. These nonlinear imaging techniques are extremely useful for biological studies on various scales from molecules to cells to tissues. Nevertheless, in most cases, nonlinear optical interaction requires strong illumination, typically at least gigawatts per square centimeter intensity. Such strong illumination can cause significant phototoxicity or even photodamage to fragile biological samples. Therefore, it is highly desirable to find mechanisms that allow the reduction of illumination intensity. Surface plasmon, which is the collective oscillation of electrons in metal under light excitation, is capable of significantly enhancing the local field around the metal nanostructures and thus boosting up the efficiency of nonlinear optical interactions of the surrounding materials or of the metal itself. In this mini-review, we discuss the recent progress of plasmonics in nonlinear optical microscopy with a special focus on biological applications. The advancement of nonlinear imaging modalities (including incoherent/coherent Raman scattering, two/three-photon luminescence, and second/third harmonic generations that have been amalgamated with plasmonics), as well as the novel subdiffraction limit imaging techniques based on nonlinear behaviors of plasmonic scattering, is addressed.

  17. Nonlinear plasmonic imaging techniques and their biological applications

    Directory of Open Access Journals (Sweden)

    Deka Gitanjal

    2016-07-01

    Full Text Available Nonlinear optics, when combined with microscopy, is known to provide advantages including novel contrast, deep tissue observation, and minimal invasiveness. In addition, special nonlinearities, such as switch on/off and saturation, can enhance the spatial resolution below the diffraction limit, revolutionizing the field of optical microscopy. These nonlinear imaging techniques are extremely useful for biological studies on various scales from molecules to cells to tissues. Nevertheless, in most cases, nonlinear optical interaction requires strong illumination, typically at least gigawatts per square centimeter intensity. Such strong illumination can cause significant phototoxicity or even photodamage to fragile biological samples. Therefore, it is highly desirable to find mechanisms that allow the reduction of illumination intensity. Surface plasmon, which is the collective oscillation of electrons in metal under light excitation, is capable of significantly enhancing the local field around the metal nanostructures and thus boosting up the efficiency of nonlinear optical interactions of the surrounding materials or of the metal itself. In this mini-review, we discuss the recent progress of plasmonics in nonlinear optical microscopy with a special focus on biological applications. The advancement of nonlinear imaging modalities (including incoherent/coherent Raman scattering, two/three-photon luminescence, and second/third harmonic generations that have been amalgamated with plasmonics, as well as the novel subdiffraction limit imaging techniques based on nonlinear behaviors of plasmonic scattering, is addressed.

  18. Spectral-Spatial Hyperspectral Image Classification Based on KNN

    Science.gov (United States)

    Huang, Kunshan; Li, Shutao; Kang, Xudong; Fang, Leyuan

    2016-12-01

    Fusion of spectral and spatial information is an effective way in improving the accuracy of hyperspectral image classification. In this paper, a novel spectral-spatial hyperspectral image classification method based on K nearest neighbor (KNN) is proposed, which consists of the following steps. First, the support vector machine is adopted to obtain the initial classification probability maps which reflect the probability that each hyperspectral pixel belongs to different classes. Then, the obtained pixel-wise probability maps are refined with the proposed KNN filtering algorithm that is based on matching and averaging nonlocal neighborhoods. The proposed method does not need sophisticated segmentation and optimization strategies while still being able to make full use of the nonlocal principle of real images by using KNN, and thus, providing competitive classification with fast computation. Experiments performed on two real hyperspectral data sets show that the classification results obtained by the proposed method are comparable to several recently proposed hyperspectral image classification methods.

  19. Spatial and spectral imaging of LMA photonic crystal fiber amplifiers

    DEFF Research Database (Denmark)

    Laurila, Marko; Lægsgaard, Jesper; Alkeskjold, Thomas Tanggaard

    2011-01-01

    We demonstrate modal characterization using spatial and spectral resolved (S2) imaging, on an Ytterbium-doped large-mode-area photonic crystal fiber (PCF) amplifier and compare results with conventional cut-off methods. We apply numerical simulations and step-index fiber experiments to calibrate...

  20. Tomato sorting using independent component analysis on spectral images

    NARCIS (Netherlands)

    Polder, G.; Heijden, van der G.W.A.M.; Young, I.T.

    2003-01-01

    Independent Component Analysis is one of the most widely used methods for blind source separation. In this paper we use this technique to estimate the most important compounds which play a role in the ripening of tomatoes. Spectral images of tomatoes were analyzed. Two main independent components

  1. AMARSI: Aerosol modeling and retrieval from multi-spectral imagers

    NARCIS (Netherlands)

    Leeuw, G. de; Curier, R.L.; Staroverova, A.; Kokhanovsky, A.; Hoyningen-Huene, W. van; Rozanov, V.V.; Burrows, J.P.; Hesselmans, G.; Gale, L.; Bouvet, M.

    2008-01-01

    The AMARSI project aims at the development and validation of aerosol retrieval algorithms over ocean. One algorithm will be developed for application with data from the Multi Spectral Imager (MSI) on EarthCARE. A second algorithm will be developed using the combined information from AATSR and MERIS,

  2. Aerosol mapping over land with imaging spectroscopy using spectral autocorrelation

    NARCIS (Netherlands)

    Bojinski, S.; Schlapfer, D.; Schaepman, M.E.; Keller, J.; Itten, K.I.

    2004-01-01

    A new method for aerosol retrieval over land is proposed that makes explicit use of the contiguous, high-resolution spectral coverage of imaging spectrometers. The method is labelled Aerosol Retrieval by Interrelated Abundances (ARIA) and is based on unmixing of the short-wave infrared sensor signal

  3. Spatial, Temporal and Spectral Satellite Image Fusion via Sparse Representation

    Science.gov (United States)

    Song, Huihui

    Remote sensing provides good measurements for monitoring and further analyzing the climate change, dynamics of ecosystem, and human activities in global or regional scales. Over the past two decades, the number of launched satellite sensors has been increasing with the development of aerospace technologies and the growing requirements on remote sensing data in a vast amount of application fields. However, a key technological challenge confronting these sensors is that they tradeoff between spatial resolution and other properties, including temporal resolution, spectral resolution, swath width, etc., due to the limitations of hardware technology and budget constraints. To increase the spatial resolution of data with other good properties, one possible cost-effective solution is to explore data integration methods that can fuse multi-resolution data from multiple sensors, thereby enhancing the application capabilities of available remote sensing data. In this thesis, we propose to fuse the spatial resolution with temporal resolution and spectral resolution, respectively, based on sparse representation theory. Taking the study case of Landsat ETM+ (with spatial resolution of 30m and temporal resolution of 16 days) and MODIS (with spatial resolution of 250m ~ 1km and daily temporal resolution) reflectance, we propose two spatial-temporal fusion methods to combine the fine spatial information of Landsat image and the daily temporal resolution of MODIS image. Motivated by that the images from these two sensors are comparable on corresponding bands, we propose to link their spatial information on available Landsat- MODIS image pair (captured on prior date) and then predict the Landsat image from the MODIS counterpart on prediction date. To well-learn the spatial details from the prior images, we use a redundant dictionary to extract the basic representation atoms for both Landsat and MODIS images based on sparse representation. Under the scenario of two prior Landsat

  4. Conjugate Etalon Spectral Imager (CESI) & Scanning Etalon Methane Mapper (SEMM) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — The Conjugate Etalon Spectral Imaging (CESI) concept enables the development of miniature instruments with high spectral resolution, suitable for LEO missions aboard...

  5. Nonlinear unmixing of hyperspectral images: models and algorithms

    CERN Document Server

    Dobigeon, Nicolas; Richard, Cédric; Bermudez, José C M; McLaughlin, Stephen; Hero, Alfred O

    2013-01-01

    When considering the problem of unmixing hyperspectral images, most of the literature in the geoscience and image processing areas rely on the widely acknowledged linear mixing model (LMM). However, in specific but common contexts, the LMM may be not valid and other nonlinear models should be invoked. Consequently, over the last few years, several significant contributions have been proposed to overcome the limitations inherent in the LMM. In this paper, we present an overview of recent advances that deal with the nonlinear unmixing problem. The main nonlinear models are introduced and their validity discussed. Then, we describe the main classes of unmixing strategies designed to solve the problem in supervised and unsupervised frameworks. Finally, the problem of detecting nonlinear mixtures in hyperspectral images is addressed.

  6. Lossless compression of multispectral images using spectral information

    Science.gov (United States)

    Ma, Long; Shi, Zelin; Tang, Xusheng

    2009-10-01

    Multispectral images are available for different purposes due to developments in spectral imaging systems. The sizes of multispectral images are enormous. Thus transmission and storage of these volumes of data require huge time and memory resources. That is why compression algorithms must be developed. A salient property of multispectral images is that strong spectral correlation exists throughout almost all bands. This fact is successfully used to predict each band based on the previous bands. We propose to use spectral linear prediction and entropy coding with context modeling for encoding multispectral images. Linear prediction predicts the value for the next sample and computes the difference between predicted value and the original value. This difference is usually small, so it can be encoded with less its than the original value. The technique implies prediction of each image band by involving number of bands along the image spectra. Each pixel is predicted using information provided by pixels in the previous bands in the same spatial position. As done in the JPEG-LS, the proposed coder also represents the mapped residuals by using an adaptive Golomb-Rice code with context modeling. This residual coding is context adaptive, where the context used for the current sample is identified by a context quantization function of the three gradients. Then, context-dependent Golomb-Rice code and bias parameters are estimated sample by sample. The proposed scheme was compared with three algorithms applied to the lossless compression of multispectral images, namely JPEG-LS, Rice coding, and JPEG2000. Simulation tests performed on AVIRIS images have demonstrated that the proposed compression scheme is suitable for multispectral images.

  7. Retinal oxygen saturation evaluation by multi-spectral fundus imaging

    Science.gov (United States)

    Khoobehi, Bahram; Ning, Jinfeng; Puissegur, Elise; Bordeaux, Kimberly; Balasubramanian, Madhusudhanan; Beach, James

    2007-03-01

    Purpose: To develop a multi-spectral method to measure oxygen saturation of the retina in the human eye. Methods: Five Cynomolgus monkeys with normal eyes were anesthetized with intramuscular ketamine/xylazine and intravenous pentobarbital. Multi-spectral fundus imaging was performed in five monkeys with a commercial fundus camera equipped with a liquid crystal tuned filter in the illumination light path and a 16-bit digital camera. Recording parameters were controlled with software written specifically for the application. Seven images at successively longer oxygen-sensing wavelengths were recorded within 4 seconds. Individual images for each wavelength were captured in less than 100 msec of flash illumination. Slightly misaligned images of separate wavelengths due to slight eye motion were registered and corrected by translational and rotational image registration prior to analysis. Numerical values of relative oxygen saturation of retinal arteries and veins and the underlying tissue in between the artery/vein pairs were evaluated by an algorithm previously described, but which is now corrected for blood volume from averaged pixels (n > 1000). Color saturation maps were constructed by applying the algorithm at each image pixel using a Matlab script. Results: Both the numerical values of relative oxygen saturation and the saturation maps correspond to the physiological condition, that is, in a normal retina, the artery is more saturated than the tissue and the tissue is more saturated than the vein. With the multi-spectral fundus camera and proper registration of the multi-wavelength images, we were able to determine oxygen saturation in the primate retinal structures on a tolerable time scale which is applicable to human subjects. Conclusions: Seven wavelength multi-spectral imagery can be used to measure oxygen saturation in retinal artery, vein, and tissue (microcirculation). This technique is safe and can be used to monitor oxygen uptake in humans. This work

  8. Experimental and theoretical studies of spectral alteration in ultrasonic waves resulting from nonlinear elastic response in rock

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, P.A.; McCall, K.R.; Meegan, G.D. Jr.

    1993-01-01

    Experiments in rock show a large nonlinear elastic wave response, far greater than that of gases, liquids and most other solids. The large response is attributed to structural defects in rock including microcracks and grain boundaries. In the earth, a large nonlinear response may be responsible for significant spectral alteration at amplitudes and distances currently considered to be well within the linear elastic regime.

  9. Experimental and theoretical studies of spectral alteration in ultrasonic waves resulting from nonlinear elastic response in rock

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, P.A.; McCall, K.R.; Meegan, G.D. Jr.

    1993-06-01

    Experiments in rock show a large nonlinear elastic wave response, far greater than that of gases, liquids and most other solids. The large response is attributed to structural defects in rock including microcracks and grain boundaries. In the earth, a large nonlinear response may be responsible for significant spectral alteration at amplitudes and distances currently considered to be well within the linear elastic regime.

  10. Experimental and theoretical studies of spectral alteration in ultrasonic waves resulting from nonlinear elastic response in rock

    Energy Technology Data Exchange (ETDEWEB)

    Johnson, P.A.; McCall, K.R.; Meegan, G.D. Jr. [Los Alamos National Lab., NM (United States)

    1993-11-01

    Experiments in rock show a large nonlinear elastic wave response, far greater than that of gases, liquids and most other solids. The large response is attributed to structural defects in rock including microcracks and grain boundaries. In the earth, a large nonlinear response may be responsible for significant spectral alteration at amplitudes and distances currently considered to be well within the linear elastic regime.

  11. Spectral and nonlinear optical studies of Propane-1, 3-diaminium nitrate

    Science.gov (United States)

    Ayadi, R.; Lhoste, J.; Ngo, H. M.; Ledoux-Rak, I.; Mhiri, T.; Boujelbene, M.

    2016-08-01

    Propane-1, 3-diaminium nitrate [C3H12N2] (NO3)2 (PDAN), an hybrid organic-inorganic nonlinear optical material combining an acentric octupolar moiety (nitrate) with a centrosymmetric organic molecule (Propane-1, 3-diaminium) was prepared by slow evaporation technique at room temperature from its aqueous solution. Good quality and well-developed crystals of size 0.133 mm×0.092 mm×0.078 mm were harvested from the mother solution. The grown single crystals were characterized for their spectral, thermal, linear and second order nonlinear optical properties. Solid-state 13C and 1H MAS-NMR spectroscopies are in agreement with the X-ray structure. The decomposition of the title compound is confirmed by the thermogravimetric analysis (TGA). The UV-visible absorption spectrum, show that PDAN is suitable for frequency doubling applications in a wide spectral range in the visible and near IR. The NLO response of the crystal was evaluated using a SHG powder technique, indicating an effective quadratic nonlinear coefficient two times higher than that of KDP in spite of the low hyperpolarizability of the nitrate ion and of the centrosymmetric character of the diaminium derivative.

  12. Compensating focusing for space hyper spectral imager's fore optical system

    Institute of Scientific and Technical Information of China (English)

    Yicha Zhang; Wei Liu

    2011-01-01

    @@ The performance of space hyper spectral imager is severely affected by turbulent orbit temperature. Turbulence results in a defocus in the fore optical system of the imager. To address this problem, a focusing system is added. A number of simulation methods are applied on the fore optical system to study the relationship between temperature and focusing. In addition, this process is conducted to obtain a practical reference for focusing while the imager is flying on orbit. The obtained correlation between focusing and temperature is proven effective based on ground imaging and simulation testing.%The performance of space hyper spectral imager is severely affected by turbulent orbit temperature. Turbulence results in a defocus in the fore optical system of the imager. To address this problem, a focusing system is added. A number of simulation methods are applied on the fore optical system to study the relationship between temperature and focusing. In addition, this process is conducted to obtain a practical reference for focusing while the imager is flying on orbit. The obtained correlation between focusing and temperature is proven effective based on ground imaging and simulation testing.

  13. Multi spectral imaging analysis for meat spoilage discrimination

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

    with corresponding sensory data would be of great interest. The purpose of this research was to produce a method capable of quantifying and/or predicting the spoilage status (e.g. express in TVC counts as well as on sensory evaluation) using a multi spectral image of a meat sample and thereby avoid any time...... classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat...... samples. In the case where all data were taken together the misclassification error amounted to 16%. When spoilage status was based on visual sensory data, the model produced a MER of 22% for the combined dataset. These results suggest that it is feasible to employ a multi spectral image...

  14. Spectral embedding finds meaningful (relevant structure in image and microarray data

    Directory of Open Access Journals (Sweden)

    Solka Jeffrey L

    2006-02-01

    Full Text Available Abstract Background Accurate methods for extraction of meaningful patterns in high dimensional data have become increasingly important with the recent generation of data types containing measurements across thousands of variables. Principal components analysis (PCA is a linear dimensionality reduction (DR method that is unsupervised in that it relies only on the data; projections are calculated in Euclidean or a similar linear space and do not use tuning parameters for optimizing the fit to the data. However, relationships within sets of nonlinear data types, such as biological networks or images, are frequently mis-rendered into a low dimensional space by linear methods. Nonlinear methods, in contrast, attempt to model important aspects of the underlying data structure, often requiring parameter(s fitting to the data type of interest. In many cases, the optimal parameter values vary when different classification algorithms are applied on the same rendered subspace, making the results of such methods highly dependent upon the type of classifier implemented. Results We present the results of applying the spectral method of Lafon, a nonlinear DR method based on the weighted graph Laplacian, that minimizes the requirements for such parameter optimization for two biological data types. We demonstrate that it is successful in determining implicit ordering of brain slice image data and in classifying separate species in microarray data, as compared to two conventional linear methods and three nonlinear methods (one of which is an alternative spectral method. This spectral implementation is shown to provide more meaningful information, by preserving important relationships, than the methods of DR presented for comparison. Tuning parameter fitting is simple and is a general, rather than data type or experiment specific approach, for the two datasets analyzed here. Tuning parameter optimization is minimized in the DR step to each subsequent

  15. Prostate cancer spectral multifeature analysis using TRUS images.

    Science.gov (United States)

    Mohamed, S S; Salama, M A

    2008-04-01

    This paper focuses on extracting and analyzing different spectral features from transrectal ultrasound (TRUS) images for prostate cancer recognition. First, the information about the images' frequency domain features and spatial domain features are combined using a Gabor filter and then integrated with the expert radiologist's information to identify the highly suspicious regions of interest (ROIs). The next stage of the proposed algorithm is to scan each identified region in order to generate the corresponding 1-D signal that represents each region. For each ROI, possible spectral feature sets are constructed using different new geometrical features extracted from the power spectrum density (PSD) of each region's signal. Next, a classifier-based algorithm for feature selection using particle swarm optimization (PSO) is adopted and used to select the optimal feature subset from the constructed feature sets. A new spectral feature set for the TRUS images using estimation of signal parameters via rotational invariance technique (ESPRIT) is also constructed, and its ability to represent tissue texture is compared to the PSD-based spectral feature sets using the support vector machines (SVMs) classifier. The accuracy obtained ranges from 72.2% to 94.4%, with the best accuracy achieved by the ESPRIT feature set.

  16. Czerny-Turner imaging spectrometer for broadband spectral simultaneity

    Institute of Scientific and Technical Information of China (English)

    Qingsheng Xue; Shurong Wang; Futian Li

    2009-01-01

    A modified asymmetrical Czerny-Turner arrangement with a fixed plane grating is proposed to correct aberrations over a broadband spectral range by analyzing the dependence of aberrations for different wavelengths.The principle of design is deduced in detail.We compare the performance of this modified Czerny-Turner imaging spectrometer with that of the existing Czerny-Turner arrangement by using a practical Czerny-Turner imaging spectrometer example.The excellent performance of the modified imaging spectrometer is confirmed by simulation with ZEMAX software.

  17. Multiphoton autofluorescence spectral analysis for fungus imaging and identification

    Science.gov (United States)

    Lin, Sung-Jan; Tan, Hsin-Yuan; Kuo, Chien-Jui; Wu, Ruei-Jr; Wang, Shiou-Han; Chen, Wei-Liang; Jee, Shiou-Hwa; Dong, Chen-Yuan

    2009-07-01

    We performed multiphoton imaging on fungi of medical significance. Fungal hyphae and spores of Aspergillus flavus, Micosporum gypseum, Micosoprum canis, Trichophyton rubrum, and Trichophyton tonsurans were found to be strongly autofluorescent but generate less prominent second harmonic signal. The cell wall and septum of fungal hyphae can be easily identified by autofluorescence imaging. We found that fungi of various species have distinct autofluorescence characteristics. Our result shows that the combination of multiphoton imaging and spectral analysis can be used to visualize and identify fungal species. This approach may be developed into an effective diagnostic tool for fungal identification.

  18. Room temperature mid-IR single photon spectral imaging

    DEFF Research Database (Denmark)

    Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter; Pedersen, Christian

    2012-01-01

    modern Quantum cascade lasers have evolved as ideal coherent mid-IR excitation sources, simple, low noise, room temperature detectors and imaging systems still lag behind. We address this need presenting a novel, field-deployable, upconversion system for sensitive, 2-D, mid-IR spectral imaging. Measured...... room temperature dark noise is 0.2 photons/spatial element/second, which is a billion times below the dark noise level of cryogenically cooled InSb cameras. Single photon imaging and up to 200 x 100 spatial elements resolution is obtained reaching record high continuous wave quantum efficiency of about...

  19. Generalization of spectral fidelity with flexible measures for the sparse representation classification of hyperspectral images

    Science.gov (United States)

    Wu, Bo; Zhu, Yong; Huang, Xin; Li, Jiayi

    2016-10-01

    Sparse representation classification (SRC) is becoming a promising tool for hyperspectral image (HSI) classification, where the Euclidean spectral distance (ESD) is widely used to reflect the fidelity between the original and reconstructed signals. In this paper, a generalized model is proposed to extend SRC by characterizing the spectral fidelity with flexible similarity measures. To validate the flexibility, several typical similarity measures-the spectral angle similarity (SAS), spectral information divergence (SID), the structural similarity index measure (SSIM), and the ESD-are included in the generalized model. Furthermore, a general solution based on a gradient descent technique is used to solve the nonlinear optimization problem formulated by the flexible similarity measures. To test the generalized model, two actual HSIs were used, and the experimental results confirm the ability of the proposed model to accommodate the various spectral similarity measures. Performance comparisons with the ESD, SAS, SID, and SSIM criteria were also conducted, and the results consistently show the advantages of the generalized model for HSI classification in terms of overall accuracy and kappa coefficient.

  20. In vivo multimodal nonlinear optical imaging of mucosal tissue

    Science.gov (United States)

    Sun, Ju; Shilagard, Tuya; Bell, Brent; Motamedi, Massoud; Vargas, Gracie

    2004-05-01

    We present a multimodal nonlinear imaging approach to elucidate microstructures and spectroscopic features of oral mucosa and submucosa in vivo. The hamster buccal pouch was imaged using 3-D high resolution multiphoton and second harmonic generation microscopy. The multimodal imaging approach enables colocalization and differentiation of prominent known spectroscopic and structural features such as keratin, epithelial cells, and submucosal collagen at various depths in tissue. Visualization of cellular morphology and epithelial thickness are in excellent agreement with histological observations. These results suggest that multimodal nonlinear optical microscopy can be an effective tool for studying the physiology and pathology of mucosal tissue.

  1. Impact of amplitude jitter and signal-to-noise ratio on the nonlinear spectral compression in optical fibres

    Science.gov (United States)

    Boscolo, Sonia; Fatome, Julien; Finot, Christophe

    2017-04-01

    We numerically study the effects of amplitude fluctuations and signal-to-noise ratio degradation of the seed pulses on the spectral compression process arising from nonlinear propagation in an optical fibre. The unveiled quite good stability of the process against these pulse degradation factors is assessed in the context of optical regeneration of intensity-modulated signals, by combining nonlinear spectral compression with centered bandpass optical filtering. The results show that the proposed nonlinear processing scheme indeed achieves mitigation of the signal's amplitude noise. However, in the presence of a jitter of the temporal duration of the pulses, the performance of the device deteriorates. © 2016 Elsevier

  2. On the Bivariate Spectral Homotopy Analysis Method Approach for Solving Nonlinear Evolution Partial Differential Equations

    Directory of Open Access Journals (Sweden)

    S. S. Motsa

    2014-01-01

    Full Text Available This paper presents a new application of the homotopy analysis method (HAM for solving evolution equations described in terms of nonlinear partial differential equations (PDEs. The new approach, termed bivariate spectral homotopy analysis method (BISHAM, is based on the use of bivariate Lagrange interpolation in the so-called rule of solution expression of the HAM algorithm. The applicability of the new approach has been demonstrated by application on several examples of nonlinear evolution PDEs, namely, Fisher’s, Burgers-Fisher’s, Burger-Huxley’s, and Fitzhugh-Nagumo’s equations. Comparison with known exact results from literature has been used to confirm accuracy and effectiveness of the proposed method.

  3. A stabilised nodal spectral element method for fully nonlinear water waves

    Science.gov (United States)

    Engsig-Karup, A. P.; Eskilsson, C.; Bigoni, D.

    2016-08-01

    We present an arbitrary-order spectral element method for general-purpose simulation of non-overturning water waves, described by fully nonlinear potential theory. The method can be viewed as a high-order extension of the classical finite element method proposed by Cai et al. (1998) [5], although the numerical implementation differs greatly. Features of the proposed spectral element method include: nodal Lagrange basis functions, a general quadrature-free approach and gradient recovery using global L2 projections. The quartic nonlinear terms present in the Zakharov form of the free surface conditions can cause severe aliasing problems and consequently numerical instability for marginally resolved or very steep waves. We show how the scheme can be stabilised through a combination of over-integration of the Galerkin projections and a mild spectral filtering on a per element basis. This effectively removes any aliasing driven instabilities while retaining the high-order accuracy of the numerical scheme. The additional computational cost of the over-integration is found insignificant compared to the cost of solving the Laplace problem. The model is applied to several benchmark cases in two dimensions. The results confirm the high order accuracy of the model (exponential convergence), and demonstrate the potential for accuracy and speedup. The results of numerical experiments are in excellent agreement with both analytical and experimental results for strongly nonlinear and irregular dispersive wave propagation. The benefit of using a high-order - possibly adapted - spatial discretisation for accurate water wave propagation over long times and distances is particularly attractive for marine hydrodynamics applications.

  4. Multi-material decomposition of spectral CT images

    Science.gov (United States)

    Mendonça, Paulo R. S.; Bhotika, Rahul; Maddah, Mahnaz; Thomsen, Brian; Dutta, Sandeep; Licato, Paul E.; Joshi, Mukta C.

    2010-04-01

    Spectral Computed Tomography (Spectral CT), and in particular fast kVp switching dual-energy computed tomography, is an imaging modality that extends the capabilities of conventional computed tomography (CT). Spectral CT enables the estimation of the full linear attenuation curve of the imaged subject at each voxel in the CT volume, instead of a scalar image in Hounsfield units. Because the space of linear attenuation curves in the energy ranges of medical applications can be accurately described through a two-dimensional manifold, this decomposition procedure would be, in principle, limited to two materials. This paper describes an algorithm that overcomes this limitation, allowing for the estimation of N-tuples of material-decomposed images. The algorithm works by assuming that the mixing of substances and tissue types in the human body has the physicochemical properties of an ideal solution, which yields a model for the density of the imaged material mix. Under this model the mass attenuation curve of each voxel in the image can be estimated, immediately resulting in a material-decomposed image triplet. Decomposition into an arbitrary number of pre-selected materials can be achieved by automatically selecting adequate triplets from an application-specific material library. The decomposition is expressed in terms of the volume fractions of each constituent material in the mix; this provides for a straightforward, physically meaningful interpretation of the data. One important application of this technique is in the digital removal of contrast agent from a dual-energy exam, producing a virtual nonenhanced image, as well as in the quantification of the concentration of contrast observed in a targeted region, thus providing an accurate measure of tissue perfusion.

  5. Online Unmixing of Multitemporal Hyperspectral Images Accounting for Spectral Variability.

    Science.gov (United States)

    Thouvenin, Pierre-Antoine; Dobigeon, Nicolas; Tourneret, Jean-Yves

    2016-09-01

    Hyperspectral unmixing is aimed at identifying the reference spectral signatures composing a hyperspectral image and their relative abundance fractions in each pixel. In practice, the identified signatures may vary spectrally from an image to another due to varying acquisition conditions, thus inducing possibly significant estimation errors. Against this background, the hyperspectral unmixing of several images acquired over the same area is of considerable interest. Indeed, such an analysis enables the endmembers of the scene to be tracked and the corresponding endmember variability to be characterized. Sequential endmember estimation from a set of hyperspectral images is expected to provide improved performance when compared with methods analyzing the images independently. However, the significant size of the hyperspectral data precludes the use of batch procedures to jointly estimate the mixture parameters of a sequence of hyperspectral images. Provided that each elementary component is present in at least one image of the sequence, we propose to perform an online hyperspectral unmixing accounting for temporal endmember variability. The online hyperspectral unmixing is formulated as a two-stage stochastic program, which can be solved using a stochastic approximation. The performance of the proposed method is evaluated on synthetic and real data. Finally, a comparison with independent unmixing algorithms illustrates the interest of the proposed strategy.

  6. Hierarchical Non-linear Image Registration Integrating Deformable Segmentation

    Institute of Scientific and Technical Information of China (English)

    RAN Xin; QI Fei-hu

    2005-01-01

    A hierarchical non-linear method for image registration was presented, which integrates image segmentation and registration under a variational framework. An improved deformable model is used to simultaneously segment and register feature from multiple images. The objects in the image pair are segmented by evolving a single contour and meanwhile the parameters of affine registration transformation are found out. After that, a contour-constrained elastic registration is applied to register the images correctly. The experimental results indicate that the proposed approach is effective to segment and register medical images.

  7. Numerical Solution of Nonlinear Fredholm Integro-Differential Equations Using Spectral Homotopy Analysis Method

    Directory of Open Access Journals (Sweden)

    Z. Pashazadeh Atabakan

    2013-01-01

    Full Text Available Spectral homotopy analysis method (SHAM as a modification of homotopy analysis method (HAM is applied to obtain solution of high-order nonlinear Fredholm integro-differential problems. The existence and uniqueness of the solution and convergence of the proposed method are proved. Some examples are given to approve the efficiency and the accuracy of the proposed method. The SHAM results show that the proposed approach is quite reasonable when compared to homotopy analysis method, Lagrange interpolation solutions, and exact solutions.

  8. Spectral transformations in the regime of pulse self-trapping in a nonlinear photonic crystal

    CERN Document Server

    Novitsky, Denis

    2011-01-01

    We consider interaction of a femtosecond light pulse with a one-dimensional photonic crystal with relaxing cubic nonlinearity in the regime of self-trapping. By use of numerical simulations, it is shown that, under certain conditions, the spectra of reflected and transmitted light possess the properties of narrow-band (quasi-monochromatic) or wide-band (continuum-like) radiation. It is remarkable that these spectral features appear due to a significant frequency shift and occur inside a photonic band gap of the structure under investigation.

  9. Spectral characterization of a frequency comb based on cascaded quadratic nonlinearities inside an optical parametric oscillator

    CERN Document Server

    Ulvila, Ville; Halonen, Lauri; Vainio, Markku

    2015-01-01

    We present an experimental study of optical frequency comb generation based on cascaded quadratic nonlinearities inside a continuous-wave-pumped optical parametric oscillator. We demonstrate comb states which produce narrow-linewidth intermode beat note signals, and we verify the mode spacing uniformity of the comb at the Hz level. We also show that spectral quality of the comb can be improved by modulating the parametric gain at a frequency that corresponds to the comb mode spacing. We have reached a high average output power of over 4 W in the near-infrared region, at ~2 {\\mu}m.

  10. Room temperature mid-IR single photon spectral imaging

    CERN Document Server

    Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter

    2012-01-01

    Spectral imaging and detection of mid-infrared (mid-IR) wavelengths are emerging as an enabling technology of great technical and scientific interest; primarily because important chemical compounds display unique and strong mid-IR spectral fingerprints revealing valuable chemical information. While modern Quantum cascade lasers have evolved as ideal coherent mid-IR excitation sources, simple, low noise, room temperature detectors and imaging systems still lag behind. We address this need presenting a novel, field-deployable, upconversion system for sensitive, 2-D, mid-IR spectral imaging. Measured room temperature dark noise is 0.2 photons/spatial element/second, which is a billion times below the dark noise level of cryogenically cooled InSb cameras. Single photon imaging and up to 200 x 100 spatial elements resolution is obtained reaching record high continuous wave quantum efficiency of about 20 % for polarized incoherent light at 3 \\mum. The proposed method is relevant for existing and new mid-IR applicat...

  11. Far ultraviolet imaging from the IMAGE spacecraft. 3. Spectral imaging of Lyman-alpha and OI 135.6 nm

    OpenAIRE

    Mende, S. B.; Heetderks, H.; H. U. Frey; Stock, J. M.; Lampton, M.; Geller, S. P.; Abiad, R.; Siegmund, O. H. W.; Habraken, Serge; Renotte, Etienne; Jamar, Claude; Rochus, Pierre; Gérard, Jean-Claude; Sigler, R.; Lauche, H.

    2000-01-01

    Two FUV Spectral imaging instruments, the Spectrographic Imager (SI) and the Geocorona Photometer (GEO) provide IMAGE with simultaneous global maps of the hydrogen (121.8 nm) and oxygen 135.6 nm components of the terrestrial aurora and with observations of the three dimensional distribution of neutral hydrogen in the magnetosphere (121.6 nm). The SI is a novel instrument type, in which spectral separation and imaging functions are independent of each other. In this instrument, two-dimensional...

  12. Images and Spectral Performance of WFC3 Interference Filters

    Science.gov (United States)

    Quijada, Manuel A.; Boucarut, R.; Telfer, R.; Baggett, S.; Quijano, J. Kim; Allen, George; Arsenovic, Peter

    2006-01-01

    The Wide Field Camera 3 (WFC3) is a panchromatic imager that will be deployed in the Hubble Space Telescope (HST). The mission of the WFC3 is to enhance HST1s imaging capability in the ultraviolet, visible and near-infrared spectral regions. Together with a wavelength coverage spanning 2000A to 1.7 micron, the WFC3 high sensitivity, high spatial resolution, and large field-of-view provide the astronomer with an unprecedented set of tools for exploring all types of exciting astrophysical terrain and for addressing many key questions in astronomy today. The filter compliment, which includes broad, medium, and narrow band filters, naturally reflects the diversity of astronomical programs to be targeted with WFC3. The WFC3 holds 61 UVIS filters elements, 14 IR filters, and 3 dispersive elements. During ground testing, the majority of the UVIS filters were found to exhibit excellent performance consistent with or exceeding expectations; however, a subset of filters showed considerable ghost images; some with relative intensity as high as 10-15%. Replacement filters with band-defining coatings that substantially reduce these ghost images were designed and procured. A state-of-the-art characterization setup was developed to measured the intensity of ghost images, focal shift, wedge direction , transmitted uniformity and surface feature of filters that could effect uniform flat field images. We will report on this new filter characterization methods, as well as the spectral performance measurements of the in-band transmittance and blocking.

  13. Fixed Delay Birefringence Imaging Interferometry for Spectral Drifting Surveys of an Astrocomb

    Science.gov (United States)

    Zhai, Yang; Xiao, Dong

    2015-08-01

    Astrocomb has been developed for exploring and investigation of extrasolar planets via radial velocity measurement based on Doppler spectroscopy. The energy loss, modal and speckle noise as well as non-linear output drift would degenerate the precision of astrocomb after coupling with multimode fiber. Due to its ultra-narrow spectral line space, traditional dispersion spectrometer and instrument are inapplicable investigating the beam quality and spectrum from the astrocomb. In this paper, we present a new technique based on fixed delay birefringence imaging interferometry with high throughput, high resolution and large field-of-view surveys for the spectral drift of astrocomb. This coherence system utilizes multi-optical Savart splitter and large interferometric delays to achieve the required spectral resolution. Such large interferometric delay scan usually causes a significant curvature of fringe pattern, so we update this Savart component with an extra sandwiched half-wave plate as a field-of-view compensator that enables target image and near-straight fringes for Fourier analysis can be obtained and captured by a two-dimensional CCD at the same time. Also, the instrumental design employs a secondary set of birefringent plates with opposite thermal properties to passively stabilize the system from phase drifting error caused by temperature fluctuations. Under the compensation, the spectral resolution could reach 105~106 in a narrow-band target region and the field-of-view will extend 3-5 times as large as a common interference imaging spectrometer and throughput will raise 1-2 orders of magnitude. The ultra-high spectral resolutions and field-of-view compensation principle are demonstrated experimentally.

  14. Sparse representation-based spectral clustering for SAR image segmentation

    Science.gov (United States)

    Zhang, Xiangrong; Wei, Zhengli; Feng, Jie; Jiao, Licheng

    2011-12-01

    A new method, sparse representation based spectral clustering (SC) with Nyström method, is proposed for synthetic aperture radar (SAR) image segmentation. Different from the conventional SC, this proposed technique is developed by using the sparse coefficients which obtained by solving l1 minimization problem to construct the affinity matrix and the Nyström method is applied to alleviate the segmentation process. The advantage of our proposed method is that we do not need to select the scaling parameter in the Gaussian kernel function artificially. We apply the proposed method, k-means and the classic spectral clustering algorithm with Nyström method to SAR image segmentation. The results show that compared with the other two methods, the proposed method can obtain much better segmentation results.

  15. Spectral Image Processing and Analysis of the Archimedes Palimpsest

    Science.gov (United States)

    2011-09-01

    SPECTRAL IMAGE PROCESSING AND ANALYSIS OF THE ARCHIMEDES PALIMPSEST Roger L. Easton, Jr., William A. Christens-Barry, Keith T. Knox Chester F...5988 (fax), e-mail: easton@cis.rit.edu web: www.cis.rit.edu/people/faculty/easton ABSTRACT The Archimedes Palimpsest is a 10th-century parchment...rendering. 1. SIGNIFICANCE OF THE CODEX Almost everything known about the work of Archimedes has been gleaned from three codex manuscripts. The first

  16. Multimodal nonlinear imaging of arabidopsis thaliana root cell

    Science.gov (United States)

    Jang, Bumjoon; Lee, Sung-Ho; Woo, Sooah; Park, Jong-Hyun; Lee, Myeong Min; Park, Seung-Han

    2017-07-01

    Nonlinear optical microscopy has enabled the possibility to explore inside the living organisms. It utilizes ultrashort laser pulse with long wavelength (greater than 800nm). Ultrashort pulse produces high peak power to induce nonlinear optical phenomenon such as two-photon excitation fluorescence (TPEF) and harmonic generations in the medium while maintaining relatively low average energy pre area. In plant developmental biology, confocal microscopy is widely used in plant cell imaging after the development of biological fluorescence labels in mid-1990s. However, fluorescence labeling itself affects the sample and the sample deviates from intact condition especially when labelling the entire cell. In this work, we report the dynamic images of Arabidopsis thaliana root cells. This demonstrates the multimodal nonlinear optical microscopy is an effective tool for long-term plant cell imaging.

  17. Spectral coupling issues in a two-degree-of-freedom system with clearance non-linearities

    Science.gov (United States)

    Padmanabhan, C.; Singh, R.

    1992-06-01

    In an earlier study [14], the frequency response characteristics of a multi-degree-of-freedom system with clearance non-linearities were presented. The current study is an extension of this prior work and deals specifically with the issue of dynamic interactions between resonances. The harmonic balance method, digital solutions and analog computer simulation are used to investigate a two-degree-of-freedom system under a mean load, when subjected to sinusoidal excitations. The existence of harmonic, periodic and chaotic solutions is demonstrated using digital simulation. The method of harmonic balance is employed to construct approximate solutions at the excitation frequency which are then used to classify weak, moderate and strong non-linear spectral interactions. The effects of parameters such as damping ratio, mean load, alternating load and frequency spacing between the resonances have been quantified. The applicability of the methodology is demonstrated through the following practical examples: (i) neutral gear rattle in an automotive transmission system; and (ii) steady state characteristics of a spur gear pair with backlash. In the second case, measured dynamic transmission error data at the gear mesh frequency are used to investigate spectral interactions. Limitations associated with solution methods and interaction classification schemes are also discussed.

  18. a Spatio-Spectral Camera for High Resolution Hyperspectral Imaging

    Science.gov (United States)

    Livens, S.; Pauly, K.; Baeck, P.; Blommaert, J.; Nuyts, D.; Zender, J.; Delauré, B.

    2017-08-01

    Imaging with a conventional frame camera from a moving remotely piloted aircraft system (RPAS) is by design very inefficient. Less than 1 % of the flying time is used for collecting light. This unused potential can be utilized by an innovative imaging concept, the spatio-spectral camera. The core of the camera is a frame sensor with a large number of hyperspectral filters arranged on the sensor in stepwise lines. It combines the advantages of frame cameras with those of pushbroom cameras. By acquiring images in rapid succession, such a camera can collect detailed hyperspectral information, while retaining the high spatial resolution offered by the sensor. We have developed two versions of a spatio-spectral camera and used them in a variety of conditions. In this paper, we present a summary of three missions with the in-house developed COSI prototype camera (600-900 nm) in the domains of precision agriculture (fungus infection monitoring in experimental wheat plots), horticulture (crop status monitoring to evaluate irrigation management in strawberry fields) and geology (meteorite detection on a grassland field). Additionally, we describe the characteristics of the 2nd generation, commercially available ButterflEYE camera offering extended spectral range (475-925 nm), and we discuss future work.

  19. Noninvasive dosimetry and monitoring of TTT using spectral imaging

    Science.gov (United States)

    Schuele, G.; Molnar, F. E.; Yellachich, D.; Vitkin, E.; Perelman, L. T.; Palanker, D.

    2006-02-01

    Transpupillary thermo therapy (TTT) is a slow (60 seconds) photothermal treatment of the fundus with a near-infrared (780-810nm) laser irradiating a large spot (0.5- 1. mm) on the retina. Due to high variability in ocular tissue properties and the lack of immediately observable outcome of the therapy, a real-time dosimetry is highly desirable. We found that fundus spectroscopy and spectrally-resolved imaging allow for non-invasive real-time monitoring and dosimetry of TTT. A 795nm laser was applied in rabbit eyes for 60 seconds using a 0.86mm retinal spot diameter. The fundus was illuminated with a broadband polarized light, and its reflectance spectra were measured in parallel and cross-polarizations. The fundus was also imaged in selected spectral domains. At irradiances that do not create ophthalmoscopically visible lesions the fundus reflectance increases at the wavelengths corresponding to absorption of the oxygenated blood indicating the reduced concentration of blood in the choroid. Vasoconstrictive response of the choroidal and retinal vasculature during TTT was also directly observed using spectrally-resolved imaging. At irradiances that produce ophthalmoscopically visible lesions a rapid reduction of the fundus reflectance was observed within the first 5-10 seconds of the exposure even when the visible lesions developed only by the end of the 60 second exposure. No visible lesions were produced where the laser was terminated after detection of the reduced scattering but prior to appearance of the enhanced scattering.

  20. Solar abundances with the SPICE spectral imager on Solar Orbiter

    Science.gov (United States)

    Giunta, Alessandra; Haberreiter, Margit; Peter, Hardi; Vial, Jean-Claude; Harrison, Richard; Parenti, Susanna; Innes, Davina; Schmutz, Werner; Buchlin, Eric; Chamberlin, Phillip; Thompson, William; Bocchialini, Karine; Gabriel, Alan; Morris, Nigel; Caldwell, Martin; Auchere, Frederic; Curdt, Werner; Teriaca, Luca; Hassler, Donald M.; DeForest, Craig; Hansteen, Viggo; Carlsson, Mats; Philippon, Anne; Janvier, Miho; Wimmer-Schweingruber, Robert; Griffin, Douglas; Baudin, Frederic; Davila, Joseph; Fludra, Andrzej; Waltham, Nick; Eccleston, Paul; Gottwald, Alexander; Klein, Roman; Hanley, John; Walls, Buddy; Howe, Chris; Schuehle, Udo; Gyo, Manfred; Pfiffner, Dany

    2016-07-01

    Elemental composition of the solar atmosphere and in particular abundance bias of low and high First Ionization Potential (FIP) elements are a key tracer of the source regions of the solar wind. These abundances and their spatio-temporal variations, as well as the other plasma parameters , will be derived by the SPICE (Spectral Imaging of the Coronal Environment) EUV spectral imager on the upcoming Solar Orbiter mission. SPICE is designed to provide spectroheliograms (spectral images) using a core set of emission lines arising from ions of both low-FIP and high-FIP elements. These lines are formed over a wide range of temperatures, enabling the analysis of the different layers of the solar atmosphere. SPICE will use these spectroheliograms to produce dynamic composition maps of the solar atmosphere to be compared to in-situ measurements of the solar wind composition of the same elements (i.e. O, Ne, Mg, Fe). This will provide a tool to study the connectivity between the spacecraft (the Heliosphere) and the Sun. We will discuss the SPICE capabilities for such composition measurements.

  1. Filtered gradient reconstruction algorithm for compressive spectral imaging

    Science.gov (United States)

    Mejia, Yuri; Arguello, Henry

    2017-04-01

    Compressive sensing matrices are traditionally based on random Gaussian and Bernoulli entries. Nevertheless, they are subject to physical constraints, and their structure unusually follows a dense matrix distribution, such as the case of the matrix related to compressive spectral imaging (CSI). The CSI matrix represents the integration of coded and shifted versions of the spectral bands. A spectral image can be recovered from CSI measurements by using iterative algorithms for linear inverse problems that minimize an objective function including a quadratic error term combined with a sparsity regularization term. However, current algorithms are slow because they do not exploit the structure and sparse characteristics of the CSI matrices. A gradient-based CSI reconstruction algorithm, which introduces a filtering step in each iteration of a conventional CSI reconstruction algorithm that yields improved image quality, is proposed. Motivated by the structure of the CSI matrix, Φ, this algorithm modifies the iterative solution such that it is forced to converge to a filtered version of the residual ΦTy, where y is the compressive measurement vector. We show that the filtered-based algorithm converges to better quality performance results than the unfiltered version. Simulation results highlight the relative performance gain over the existing iterative algorithms.

  2. Spectral Properties of Homogeneous and Nonhomogeneous Radar Images

    DEFF Research Database (Denmark)

    Madsen, Søren Nørvang

    1987-01-01

    On the basis of a two-dimensional, nonstationary white noisemodel for the complex radar backscatter, the spectral properties ofa one-look synthetic-aperture radar (SAR) system is derived. It isshown that the power spectrum of the complex SAR image is sceneindependent. It is also shown...... that the spectrum of the intensityimage is in general related to the radar scene spectrum by a linearintegral equation, a Fredholm's integral equation of the third kind.Under simplifying assumptions, a closed-form equation giving theradar scene spectrum as a function of the SAR image spectrum canbe derived....

  3. Spatial-spectral method for classification of hyperspectral images.

    Science.gov (United States)

    Bian, Xiaoyong; Zhang, Tianxu; Yan, Luxin; Zhang, Xiaolong; Fang, Houzhang; Liu, Hai

    2013-03-15

    Spatial-spectral approach with spatially adaptive classification of hyperspectral images is proposed. The rotation-invariant spatial texture information for each object is exploited and incorporated into the classifier by using the modified local Gabor binary pattern to distinguish different types of classes of interest. The proposed method can effectively suppress anisotropic texture in spatially separate classes as well as improve the discrimination among classes. Moreover, it becomes more robust with the within-class variation. Experimental results on the classification of three real hyperspectral remote sensing images demonstrate the effectiveness of the proposed approach.

  4. Near-infrared spectral imaging Michelson interferometer for astronomical applications

    Science.gov (United States)

    Wells, C. W.; Potter, A. E.; Morgan, T. H.

    1980-01-01

    The design and operation of an imaging Michelson interferometer-spectrometer used for near-infrared (0.8 micron to 2.5 microns) spectral imaging are reported. The system employs a rapid scan interferometer modified for stable low resolution (250/cm) performance and a 42 element PbS linear detector array. A microcomputer system is described which provides data acquisition, coadding, and Fourier transformation for near real-time presentation of the spectra of all 42 scene elements. The electronic and mechanical designs are discussed and telescope performance data presented.

  5. Hybrid Image Fusion for Sharpness Enhancement of Multi-Spectral Lunar Images

    Science.gov (United States)

    Awumah, Anna; Mahanti, Prasun; Robinson, Mark

    2016-10-01

    Image fusion enhances the sharpness of a multi-spectral (MS) image by incorporating spatial details from a higher-resolution panchromatic (Pan) image [1,2]. Known applications of image fusion for planetary images are rare, although image fusion is well-known for its applications to Earth-based remote sensing. In a recent work [3], six different image fusion algorithms were implemented and their performances were verified with images from the Lunar Reconnaissance Orbiter (LRO) Camera. The image fusion procedure obtained a high-resolution multi-spectral (HRMS) product from the LRO Narrow Angle Camera (used as Pan) and LRO Wide Angle Camera (used as MS) images. The results showed that the Intensity-Hue-Saturation (IHS) algorithm results in a high-spatial quality product while the Wavelet-based image fusion algorithm best preserves spectral quality among all the algorithms. In this work we show the results of a hybrid IHS-Wavelet image fusion algorithm when applied to LROC MS images. The hybrid method provides the best HRMS product - both in terms of spatial resolution and preservation of spectral details. Results from hybrid image fusion can enable new science and increase the science return from existing LROC images.[1] Pohl, Cle, and John L. Van Genderen. "Review article multisensor image fusion in remote sensing: concepts, methods and applications." International journal of remote sensing 19.5 (1998): 823-854.[2] Zhang, Yun. "Understanding image fusion." Photogramm. Eng. Remote Sens 70.6 (2004): 657-661.[3] Mahanti, Prasun et al. "Enhancement of spatial resolution of the LROC Wide Angle Camera images." Archives, XXIII ISPRS Congress Archives (2016).

  6. Nonlinear Filter Based Image Denoising Using AMF Approach

    CERN Document Server

    Thivakaran, T K

    2010-01-01

    This paper proposes a new technique based on nonlinear Adaptive Median filter (AMF) for image restoration. Image denoising is a common procedure in digital image processing aiming at the removal of noise, which may corrupt an image during its acquisition or transmission, while retaining its quality. This procedure is traditionally performed in the spatial or frequency domain by filtering. The aim of image enhancement is to reconstruct the true image from the corrupted image. The process of image acquisition frequently leads to degradation and the quality of the digitized image becomes inferior to the original image. Filtering is a technique for enhancing the image. Linear filter is the filtering in which the value of an output pixel is a linear combination of neighborhood values, which can produce blur in the image. Thus a variety of smoothing techniques have been developed that are non linear. Median filter is the one of the most popular non-linear filter. When considering a small neighborhood it is highly e...

  7. Spectrally optimal illuminations for diabetic retinopathy detection in retinal imaging

    Science.gov (United States)

    Bartczak, Piotr; Fält, Pauli; Penttinen, Niko; Ylitepsa, Pasi; Laaksonen, Lauri; Lensu, Lasse; Hauta-Kasari, Markku; Uusitalo, Hannu

    2017-01-01

    Retinal photography is a standard method for recording retinal diseases for subsequent analysis and diagnosis. However, the currently used white light or red-free retinal imaging does not necessarily provide the best possible visibility of different types of retinal lesions, important when developing diagnostic tools for handheld devices, such as smartphones. Using specifically designed illumination, the visibility and contrast of retinal lesions could be improved. In this study, spectrally optimal illuminations for diabetic retinopathy lesion visualization are implemented using a spectrally tunable light source based on digital micromirror device. The applicability of this method was tested in vivo by taking retinal monochrome images from the eyes of five diabetic volunteers and two non-diabetic control subjects. For comparison to existing methods, we evaluated the contrast of retinal images taken with our method and red-free illumination. The preliminary results show that the use of optimal illuminations improved the contrast of diabetic lesions in retinal images by 30-70%, compared to the traditional red-free illumination imaging.

  8. Multiscale stochastic hierarchical image segmentation by spectral clustering

    Institute of Scientific and Technical Information of China (English)

    LI XiaoBin; TIAN Zheng

    2007-01-01

    This paper proposes a sampling based hierarchical approach for solving the computational demands of the spectral clustering methods when applied to the problem of image segmentation. The authors first define the distance between a pixel and a cluster, and then derive a new theorem to estimate the number of samples needed for clustering. Finally, by introducing a scale parameter into the similarity function, a novel spectral clustering based image segmentation method has been developed. An important characteristic of the approach is that in the course of image segmentation one needs not only to tune the scale parameter to merge the small size clusters or split the large size clusters but also take samples from the data set at the different scales. The multiscale and stochastic nature makes it feasible to apply the method to very large grouping problem. In addition, it also makes the segmentation compute in time that is linear in the size of the image. The experimental results on various synthetic and real world images show the effectiveness of the approach.

  9. Biomass estimator for NIR image with a few additional spectral band images taken from light UAS

    Science.gov (United States)

    Pölönen, Ilkka; Salo, Heikki; Saari, Heikki; Kaivosoja, Jere; Pesonen, Liisa; Honkavaara, Eija

    2012-05-01

    A novel way to produce biomass estimation will offer possibilities for precision farming. Fertilizer prediction maps can be made based on accurate biomass estimation generated by a novel biomass estimator. By using this knowledge, a variable rate amount of fertilizers can be applied during the growing season. The innovation consists of light UAS, a high spatial resolution camera, and VTT's novel spectral camera. A few properly selected spectral wavelengths with NIR images and point clouds extracted by automatic image matching have been used in the estimation. The spectral wavelengths were chosen from green, red, and NIR channels.

  10. Nonlinear signaling on biological networks: The role of stochasticity and spectral clustering

    Science.gov (United States)

    Hernandez-Hernandez, Gonzalo; Myers, Jesse; Alvarez-Lacalle, Enrique; Shiferaw, Yohannes

    2017-03-01

    Signal transduction within biological cells is governed by networks of interacting proteins. Communication between these proteins is mediated by signaling molecules which bind to receptors and induce stochastic transitions between different conformational states. Signaling is typically a cooperative process which requires the occurrence of multiple binding events so that reaction rates have a nonlinear dependence on the amount of signaling molecule. It is this nonlinearity that endows biological signaling networks with robust switchlike properties which are critical to their biological function. In this study we investigate how the properties of these signaling systems depend on the network architecture. Our main result is that these nonlinear networks exhibit bistability where the network activity can switch between states that correspond to a low and high activity level. We show that this bistable regime emerges at a critical coupling strength that is determined by the spectral structure of the network. In particular, the set of nodes that correspond to large components of the leading eigenvector of the adjacency matrix determines the onset of bistability. Above this transition the eigenvectors of the adjacency matrix determine a hierarchy of clusters, defined by its spectral properties, which are activated sequentially with increasing network activity. We argue further that the onset of bistability occurs either continuously or discontinuously depending upon whether the leading eigenvector is localized or delocalized. Finally, we show that at low network coupling stochastic transitions to the active branch are also driven by the set of nodes that contribute more strongly to the leading eigenvector. However, at high coupling, transitions are insensitive to network structure since the network can be activated by stochastic transitions of a few nodes. Thus this work identifies important features of biological signaling networks that may underlie their biological

  11. Pulse-driven nonlinear Alfv\\'en waves and their role in the spectral line broadening

    CERN Document Server

    Chmielewski, P; Murawski, K; Musielak, Z E

    2012-01-01

    We study the impulsively generated non-linear Alfv\\'en waves in the solar atmosphere, and describe their most likely role in the observed non-thermal broadening of some spectral lines in solar coronal holes. We solve numerically the time-dependent magnetohydrodynamic equations to find temporal signatures of large-amplitude Alfv\\'en waves in the model atmosphere of open and expanding magnetic field configuration, with a realistic temperature distribution. We calculate the temporally and spatially averaged, instantaneous transversal velocity of non-linear Alfv\\'en waves at different heights of the model atmosphere, and estimate its contribution to the unresolved non-thermal motions caused by the waves. We find that the pulse-driven nonlinear Alfv\\'en waves with the amplitude $A_{\\rm v}$=50 km s$^{-1}$ are the most likely candidates for the non-thermal broadening of Si VIII $\\lambda$1445.75 \\AA\\ line profiles in the polar coronal hole as reported by Banerjee et al. (1998). We also demonstrate that the Alfv\\'en w...

  12. Phasor analysis of multiphoton spectral images distinguishes autofluorescence components of in vivo human skin

    NARCIS (Netherlands)

    Fereidouni, F.; Bader, A.N.; Colonna, A.; Gerritsen, H.C.

    2014-01-01

    Skin contains many autofluorescent components that can be studied using spectral imaging. We employed a spectral phasor method to analyse two photon excited auto-fluorescence and second harmonic generation images of in vivo human skin. This method allows segmentation of images based on spectral feat

  13. Accuracy in mineral identification: image spectral and spatial resolutions and mineral spectral properties

    Directory of Open Access Journals (Sweden)

    L. Pompilio

    2006-06-01

    Full Text Available Problems related to airborne hyperspectral image data are reviewed and the requirements for data analysis applied to mineralogical (rocks and soils interpretation are discussed. The variability of mineral spectral features, including absorption position, shape and depth is considered and interpreted as due to chemical composition, grain size effects and mineral association. It is also shown how this variability can be related to well defined geologic processes. The influence of sensor noise and diffuse atmospheric radiance in classification accuracy is also analyzed.

  14. Nonlinear approximation of image based on monoscale orthonormal ridgelets frame

    Institute of Scientific and Technical Information of China (English)

    Lu Chengwu; Song Yimei; Song Guoxiang

    2007-01-01

    A new tight frame called as monoscale orthonormal ridgelet frame (MORF) is proposed. The localization principle and the orthonormal ridgelet constructed by Donoho are applied to construct the MORF, which are used to evaluate the order of nonlinear approximation for image with edge. Because the new tight frame not only has directionality but also bears orthonormality. It overcomes redundancy of Candes's monoscale ridgelets and provides many excellent properties in practical application. Theoretical analysis and experiments demonstrate that the new frame has remarkable potential for image compression, image reconstruction, and image denoising with the simple refinement for MORF.

  15. Investigation on the formation of intense fringe near nonlinear medium slab in nonlinear imaging

    Science.gov (United States)

    Hu, Yonghua; Qiu, Yaqiong; Peng, Xue

    2016-11-01

    It is well known that hot images of small-scale scatterers can be formed. For phase-typed scatterers, hot image and second-order hot-image can be formed. However, when the number of scatterer is larger than one, the interaction between the scatterered waves will lead to new nonlinear propagation results. In this paper, the propagation of flat-topped intense laser beam through Kerr medium slab is investigated, with the incident beam modulated by two parallel wirelike phase-typed scatterers. We demonstrate that an intense fringe together with hot image and second-order hot image can be formed when the distance of the two scatterers is several millimeters. It is found that the on-axis position of the plane of this intense fringe is in the middle part between the exit surface of the Kerr medium slab and the secondorder hot image plane. This intense fringe shows the following basic properties: Firstly, its intensity is apparently higher than that of corresponding second-order hot image and can be comparable with that of corresponding hot image; Secondly, the distances between it and the in-beam positions of the scatterers are identical. The intensity profile shows that this intense fringe is the only prominent bright fringe in the corresponding plane, and thus it is not a nonlinear image of any scatterer. Besides, the influences of the properties of scatterer on the intensity of the fringe are discussed.

  16. Imaging of discontinuities in nonlinear 3-D seismic inversion

    Energy Technology Data Exchange (ETDEWEB)

    Carrion, P.M.; Cerveny, V. (PPPG/UFBA, Salvador (Brazil))

    1990-09-01

    The authors present a nonlinear approach for reconstruction of discontinuities in geological environment (earth's crust, say). The advantage of the proposed method is that it is not limited to a Born approximation (small angles of propagation and weak scatterers). One can expect significantly better images since larger apertures including wide angle reflection arrivals can be incorporated into the imaging operator. In this paper, they treat only compressional body waves: shear and surface waves are considered as noise.

  17. Image-based spectral transmission estimation using "sensitivity comparison".

    Science.gov (United States)

    Nahavandi, Alireza Mahmoudi; Tehran, Mohammad Amani

    2017-01-20

    Although digital cameras have been used for spectral reflectance estimation, transmission measurement has rarely been considered in studies. This study presents a method named sensitivity comparison (SC) for spectral transmission estimation. The method needs neither a priori knowledge from the samples nor statistical information of a given reflectance dataset. As with spectrophotometers, the SC method needs one shot for calibration and another shot for measurement. The method exploits the sensitivity of the camera in the absence and presence of transparent colored objects for transmission estimation. 138 Kodak Wratten Gelatin filter transmissions were used for controlling the proposed method. Using modeling of the imaging system in different levels of noise, the performance of the proposed method was compared with a training-based Matrix R method. For checking the performance of the SC method in practice, 33 manmade colored transparent films were used in a conventional three-channel camera. The method generated promising results using different error metrics.

  18. Multi-crack imaging using nonclassical nonlinear acoustic method

    Science.gov (United States)

    Zhang, Lue; Zhang, Ying; Liu, Xiao-Zhou; Gong, Xiu-Fen

    2014-10-01

    Solid materials with cracks exhibit the nonclassical nonlinear acoustical behavior. The micro-defects in solid materials can be detected by nonlinear elastic wave spectroscopy (NEWS) method with a time-reversal (TR) mirror. While defects lie in viscoelastic solid material with different distances from one another, the nonlinear and hysteretic stress—strain relation is established with Preisach—Mayergoyz (PM) model in crack zone. Pulse inversion (PI) and TR methods are used in numerical simulation and defect locations can be determined from images obtained by the maximum value. Since false-positive defects might appear and degrade the imaging when the defects are located quite closely, the maximum value imaging with a time window is introduced to analyze how defects affect each other and how the fake one occurs. Furthermore, NEWS-TR-NEWS method is put forward to improve NEWS-TR scheme, with another forward propagation (NEWS) added to the existing phases (NEWS and TR). In the added phase, scanner locations are determined by locations of all defects imaged in previous phases, so that whether an imaged defect is real can be deduced. NEWS-TR-NEWS method is proved to be effective to distinguish real defects from the false-positive ones. Moreover, it is also helpful to detect the crack that is weaker than others during imaging procedure.

  19. Dual-frequency transducer for nonlinear contrast agent imaging.

    Science.gov (United States)

    Guiroy, Axel; Novell, Anthony; Ringgaard, Erling; Lou-Moeller, Rasmus; Grégoire, Jean-Marc; Abellard, André-Pierre; Zawada, Tomasz; Bouakaz, Ayache; Levassort, Franck

    2013-12-01

    Detection of high-order nonlinear components issued from microbubbles has emerged as a sensitive method for contrast agent imaging. Nevertheless, the detection of these high-frequency components, including the third, fourth, and fifth harmonics, remains challenging because of the lack of transducer sensitivity and bandwidth. In this context, we propose a new design of imaging transducer based on a simple fabrication process for high-frequency nonlinear imaging. The transducer is composed of two elements: the outer low-frequency (LF) element was centered at 4 MHz and used in transmit mode, whereas the inner high-frequency (HF) element centered at 14 MHz was used in receive mode. The center element was pad-printed using a lead zirconate titanate (PZT) paste. The outer element was molded using a commercial PZT, and curved porous unpoled PZT was used as backing. Each piezoelectric element was characterized to determine the electromechanical performance with thickness coupling factor around 45%. After the assembly of the two transducer elements, hydrophone measurements (electroacoustic responses and radiation patterns) were carried out and demonstrated a large bandwidth (70% at -3 dB) of the HF transducer. Finally, the transducer was evaluated for contrast agent imaging using contrast agent microbubbles. The results showed that harmonic components (up to the sixth harmonic) of the microbubbles were successfully detected. Moreover, images from a flow phantom were acquired and demonstrated the potential of the transducer for high-frequency nonlinear contrast imaging.

  20. Quantitative imaging of excised osteoarthritic cartilage using spectral CT

    Energy Technology Data Exchange (ETDEWEB)

    Rajendran, Kishore; Bateman, Christopher J.; Younis, Raja Aamir; De Ruiter, Niels J.A.; Ramyar, Mohsen; Anderson, Nigel G. [University of Otago - Christchurch, Department of Radiology, Christchurch (New Zealand); Loebker, Caroline [University of Otago, Christchurch Regenerative Medicine and Tissue Engineering Group, Department of Orthopaedic Surgery and Musculoskeletal Medicine, Christchurch (New Zealand); University of Twente, Department of Developmental BioEngineering, Enschede (Netherlands); Schon, Benjamin S.; Hooper, Gary J.; Woodfield, Tim B.F. [University of Otago, Christchurch Regenerative Medicine and Tissue Engineering Group, Department of Orthopaedic Surgery and Musculoskeletal Medicine, Christchurch (New Zealand); Chernoglazov, Alex I. [University of Canterbury, Human Interface Technology Laboratory New Zealand, Christchurch (New Zealand); Butler, Anthony P.H. [University of Otago - Christchurch, Department of Radiology, Christchurch (New Zealand); European Organisation for Nuclear Research (CERN), Geneva (Switzerland); MARS Bioimaging, Christchurch (New Zealand)

    2017-01-15

    To quantify iodine uptake in articular cartilage as a marker of glycosaminoglycan (GAG) content using multi-energy spectral CT. We incubated a 25-mm strip of excised osteoarthritic human tibial plateau in 50 % ionic iodine contrast and imaged it using a small-animal spectral scanner with a cadmium telluride photon-processing detector to quantify the iodine through the thickness of the articular cartilage. We imaged both spectroscopic phantoms and osteoarthritic tibial plateau samples. The iodine distribution as an inverse marker of GAG content was presented in the form of 2D and 3D images after applying a basis material decomposition technique to separate iodine in cartilage from bone. We compared this result with a histological section stained for GAG. The iodine in cartilage could be distinguished from subchondral bone and quantified using multi-energy CT. The articular cartilage showed variation in iodine concentration throughout its thickness which appeared to be inversely related to GAG distribution observed in histological sections. Multi-energy CT can quantify ionic iodine contrast (as a marker of GAG content) within articular cartilage and distinguish it from bone by exploiting the energy-specific attenuation profiles of the associated materials. (orig.)

  1. CHOROIDAL IMAGING USING SPECTRAL-DOMAIN OPTICAL COHERENCE TOMOGRAPHY

    Science.gov (United States)

    Regatieri, Caio V.; Branchini, Lauren; Fujimoto, James G.; Duker, Jay S.

    2012-01-01

    Background A structurally and functionally normal choroidal vasculature is essential for retinal function. Therefore, a precise clinical understanding of choroidal morphology should be important for understanding many retinal and choroidal diseases. Methods PUBMED (http://www.ncbi.nlm.nih.gov/sites/entrez?db=pubmed) was used for most of the literature search for this article. The criterion for inclusion of an article in the references for this review was that it included materials about both the clinical and the basic properties of choroidal imaging using spectral-domain optical coherence tomography. Results Recent reports show successful examination and accurate measurement of choroidal thickness in normal and pathologic states using spectral-domain optical coherence tomography systems. This review focuses on the principles of the new technology that make choroidal imaging using optical coherence tomography possible and on the changes that subsequently have been documented to occur in the choroid in various diseases. Additionally, it outlines future directions in choroidal imaging. Conclusion Optical coherence tomography is now proven to be an effective noninvasive tool to evaluate the choroid and to detect choroidal changes in pathologic states. Additionally, choroidal evaluation using optical coherence tomography can be used as a parameter for diagnosis and follow-up. PMID:22487582

  2. Segmentation of dynamic PET images with kinetic spectral clustering

    Science.gov (United States)

    Mouysset, S.; Zbib, H.; Stute, S.; Girault, J. M.; Charara, J.; Noailles, J.; Chalon, S.; Buvat, I.; Tauber, C.

    2013-10-01

    Segmentation is often required for the analysis of dynamic positron emission tomography (PET) images. However, noise and low spatial resolution make it a difficult task and several supervised and unsupervised methods have been proposed in the literature to perform the segmentation based on semi-automatic clustering of the time activity curves of voxels. In this paper we propose a new method based on spectral clustering that does not require any prior information on the shape of clusters in the space in which they are identified. In our approach, the p-dimensional data, where p is the number of time frames, is first mapped into a high dimensional space and then clustering is performed in a low-dimensional space of the Laplacian matrix. An estimation of the bounds for the scale parameter involved in the spectral clustering is derived. The method is assessed using dynamic brain PET images simulated with GATE and results on real images are presented. We demonstrate the usefulness of the method and its superior performance over three other clustering methods from the literature. The proposed approach appears as a promising pre-processing tool before parametric map calculation or ROI-based quantification tasks.

  3. Extremely Nonlinear Optics Using Shaped Pulses Spectrally Broadened in an Argon- or Sulfur Hexafluoride-Filled Hollow-Core Fiber

    OpenAIRE

    Andreas Hoffmann; Michael Zürch; Christian Spielmann

    2015-01-01

    In this contribution we present a comparison of the performance of spectrally broadened ultrashort pulses using a hollow-core fiber either filled with argon or sulfur hexafluoride (SF6) for demanding pulse-shaping experiments. The benefits of both gases for pulse-shaping are studied in the highly nonlinear process of high-harmonic generation. In this setup, temporally shaping the driving laser pulse leads to spectrally shaping of the output extreme ultraviolet (XUV) spectrum, where total yie...

  4. SAR image segmentation using MSER and improved spectral clustering

    Science.gov (United States)

    Gui, Yang; Zhang, Xiaohu; Shang, Yang

    2012-12-01

    A novel approach is presented for synthetic aperture radar (SAR) image segmentation. By incorporating the advantages of maximally stable extremal regions (MSER) algorithm and spectral clustering (SC) method, the proposed approach provides effective and robust segmentation. First, the input image is transformed from a pixel-based to a region-based model by using the MSER algorithm. The input image after MSER procedure is composed of some disjoint regions. Then the regions are treated as nodes in the image plane, and a graph structure is applied to represent them. Finally, the improved SC is used to perform globally optimal clustering, by which the result of image segmentation can be generated. To avoid some incorrect partitioning when considering each region as one graph node, we assign different numbers of nodes to represent the regions according to area ratios among the regions. In addition, K-harmonic means instead of K-means is applied in the improved SC procedure in order to raise its stability and performance. Experimental results show that the proposed approach is effective on SAR image segmentation and has the advantage of calculating quickly.

  5. Piecewise nonlinear image registration using DCT basis functions

    Science.gov (United States)

    Gan, Lin; Agam, Gady

    2015-03-01

    The deformation field in nonlinear image registration is usually modeled by a global model. Such models are often faced with the problem that a locally complex deformation cannot be accurately modeled by simply increasing degrees of freedom (DOF). In addition, highly complex models require additional regularization which is usually ineffective when applied globally. Registering locally corresponding regions addresses this problem in a divide and conquer strategy. In this paper we propose a piecewise image registration approach using Discrete Cosine Transform (DCT) basis functions for a nonlinear model. The contributions of this paper are three-folds. First, we develop a multi-level piecewise registration framework that extends the concept of piecewise linear registration and works with any nonlinear deformation model. This framework is then applied to nonlinear DCT registration. Second, we show how adaptive model complexity and regularization could be applied for local piece registration, thus accounting for higher variability. Third, we show how the proposed piecewise DCT can overcome the fundamental problem of a large curvature matrix inversion in global DCT when using high degrees of freedoms. The proposed approach can be viewed as an extension of global DCT registration where the overall model complexity is increased while achieving effective local regularization. Experimental evaluation results provide comparison of the proposed approach to piecewise linear registration using an affine transformation model and a global nonlinear registration using DCT model. Preliminary results show that the proposed approach achieves improved performance.

  6. New Cardiovascular Indices Based on a Nonlinear Spectral Analysis of Arterial Blood Pressure Waveforms

    CERN Document Server

    Laleg, Taous-Meriem; Papelier, Yves; Crépeau, Emmanuelle; Sorine, Michel

    2007-01-01

    A new method for analyzing arterial blood pressure is presented in this report. The technique is based on the scattering transform and consists in solving the spectral problem associated to a one-dimensional Schr\\"odinger operator with a potential depending linearly upon the pressure. This potential is then expressed with the discrete spectrum which includes negative eigenvalues and corresponds to the interacting components of an N-soliton. The approach is similar to a nonlinear Fourier transform where the solitons play the role of sine and cosine components. The method provides new cardiovascular indices that seem to contain relevant physiological information. We first show how to use this approach to decompose the arterial blood pressure pulse into elementary waves and to reconstruct it or to separate its systolic and diastolic phases. Then we analyse the parameters computed from this technique in two physiological conditions, the head-up 60 degrees tilt test and the isometric handgrip test, widely used for...

  7. Optimization of spectral sensitivities of mosaic five-band camera for estimating chromophore densities from skin images including shading and surface reflections

    Science.gov (United States)

    Hirose, Misa; Akaho, Rina; Maita, Chikashi; Sugawara, Mai; Tsumura, Norimichi

    2016-06-01

    In this paper, the spectral sensitivities of a mosaic five-band camera were optimized using a numerical skin phantom to perform the separation of chromophore densities, shading and surface reflection. To simulate the numerical skin phantom, the spectral reflectance of skin was first calculated by Monte Carlo simulation of photon migration for different concentrations of melanin, blood and oxygen saturation levels. The melanin and hemoglobin concentration distributions used in the numerical skin phantom were obtained from actual skin images by independent component analysis. The calculated components were assigned as concentration distributions. The spectral sensitivities of the camera were then optimized using a nonlinear technique to estimate the spectral reflectance for skin separation. In this optimization, the spectral sensitivities were assumed to be normally distributed, and the sensor arrangement was identical to that of a conventional mosaic five-band camera. Our findings demonstrated that spectral estimation could be significantly improved by optimizing the spectral sensitivities.

  8. Image nonlinearity and non-uniformity corrections using Papoulis - Gerchberg algorithm in gamma imaging systems

    Science.gov (United States)

    Shemer, A.; Schwarz, A.; Gur, E.; Cohen, E.; Zalevsky, Z.

    2015-04-01

    In this paper, the authors describe a novel technique for image nonlinearity and non-uniformity corrections in imaging systems based on gamma detectors. The limitation of the gamma detector prevents the producing of high quality images due to the radionuclide distribution. This problem causes nonlinearity and non-uniformity distortions in the obtained image. Many techniques have been developed to correct or compensate for these image artifacts using complex calibration processes. The presented method is based on the Papoulis - Gerchberg(PG) iterative algorithm and is obtained without need of detector calibration, tuning process or using any special test phantom.

  9. A Kernel—based Nonlinear Subspace Projection Method for Dimensionality Reduction of Hyperspectral Image Data

    Institute of Scientific and Technical Information of China (English)

    GUYanfeng; ZHANGYe; QUANTaifan

    2003-01-01

    A challenging problem in using hyper-spectral data is to eliminate redundancy and preserve useful spectral information for applications. In this pa-per, a kernel-based nonlinear subspace projection (KNSP)method is proposed for feature extraction and dimension-ality reduction in hyperspectral images. The proposed method includes three key steps: subspace partition of hyperspectral data, feature extraction using kernel-based principal component analysis (KPCA) and feature selec-tion based on class separability in the subspaces. Accord-ing to the strong correlation between neighboring bands,the whole data space is partitioned to requested subspaces.In each subspace, the KPCA method is used to effectively extract spectral feature and eliminate redundancies. A criterion function based on class discrimination and sepa-rability is used for the transformed feature selection. For the purpose of testifying its effectiveness, the proposed new method is compared with the classical principal component analysis (PCA) and segmented principal component trans-formation (SPCT). A hyperspectral image classification is performed on AVIRIS data. which have 224 svectral bands.Experimental results show that KNSP is very effective for feature extraction and dimensionality reduction of hyper-spectral data and provides significant improvement over classical PCA and current SPCT technique.

  10. Scene matching based on non-linear pre-processing on reference image and sensed image

    Institute of Scientific and Technical Information of China (English)

    Zhong Sheng; Zhang Tianxu; Sang Nong

    2005-01-01

    To solve the heterogeneous image scene matching problem, a non-linear pre-processing method for the original images before intensity-based correlation is proposed. The result shows that the proper matching probability is raised greatly. Especially for the low S/N image pairs, the effect is more remarkable.

  11. Non-linear imaging condition to image fractures as non-welded interfaces

    NARCIS (Netherlands)

    Minato, S.; Ghose, R.

    2014-01-01

    Hydraulic properties of a fractured reservoir are often controlled by large fractures. In order to seismically detect and characterize them, a high-resolution imaging method is necessary. We apply a non-linear imaging condition to image fractures, considered as non-welded interfaces. We derive the i

  12. Generation of pulsed light in the visible spectral region based on non-linear cavity dumping

    DEFF Research Database (Denmark)

    Johansson, Sandra; Andersen, Martin; Tidemand-Lichtenberg, Peter

    We propose a novel generic approach for generation of pulsed light in the visible spectrum based on sum-frequency generation between the high circulating intra-cavity power of a high finesse CW laser and a single-passed pulsed laser. For demonstration, we used a CW 1342 nm laser mixed...... with a passively Q-switched 1064 nm laser to generate pulsed light at 593 nm. Light sources in the yellow spectral region have several applications, e.g. dermatology, laser displays and flow cytometry. Traditionally, copper-vapor lasers at 578 nm and dye lasers are used in this spectral region. These are however...... as the CW light source, using a folded cavity to achieve tight focussing in the non-linear crystal which was a 11 mm long PPKTP. The pulsed light source was a Nd:YVO4 laser emitting at 1064 nm using Cr:YAG as a passive saturable absorber, resulting in a pulse length of 100 ns and a repetition frequency...

  13. Nonlinear Legendre Spectral Finite Elements for Wind Turbine Blade Dynamics: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Q.; Sprague, M. A.; Jonkman, J.; Johnson, N.

    2014-01-01

    This paper presents a numerical implementation and examination of new wind turbine blade finite element model based on Geometrically Exact Beam Theory (GEBT) and a high-order spectral finite element method. The displacement-based GEBT is presented, which includes the coupling effects that exist in composite structures and geometric nonlinearity. Legendre spectral finite elements (LSFEs) are high-order finite elements with nodes located at the Gauss-Legendre-Lobatto points. LSFEs can be an order of magnitude more efficient that low-order finite elements for a given accuracy level. Interpolation of the three-dimensional rotation, a major technical barrier in large-deformation simulation, is discussed in the context of LSFEs. It is shown, by numerical example, that the high-order LSFEs, where weak forms are evaluated with nodal quadrature, do not suffer from a drawback that exists in low-order finite elements where the tangent-stiffness matrix is calculated at the Gauss points. Finally, the new LSFE code is implemented in the new FAST Modularization Framework for dynamic simulation of highly flexible composite-material wind turbine blades. The framework allows for fully interactive simulations of turbine blades in operating conditions. Numerical examples showing validation and LSFE performance will be provided in the final paper.

  14. Spectral evolution of weakly nonlinear random waves: kinetic description vs direct numerical simulations

    Science.gov (United States)

    Annenkov, Sergei; Shrira, Victor

    2016-04-01

    We study numerically the long-term evolution of water wave spectra without wind forcing, using three different models, aiming at understanding the role of different sets of assumptions. The first model is the classical Hasselmann kinetic equation (KE). We employ the WRT code kindly provided by G. van Vledder. Two other models are new. As the second model, we use the generalised kinetic equation (gKE), derived without the assumption of quasi-stationarity. Thus, unlike the KE, the gKE is valid in the cases when a wave spectrum is changing rapidly (e.g. at the initial stage of evolution of a narrow spectrum). However, the gKE employs the same statistical closure as the KE. The third model is based on the Zakharov integrodifferential equation for water waves and does not depend on any statistical assumptions. Since the Zakharov equation plays the role of the primitive equation of the theory of wave turbulence, we refer to this model as direct numerical simulation of spectral evolution (DNS-ZE). For initial conditions, we choose two narrow-banded spectra with the same frequency distribution (a JONSWAP spectrum with high peakedness γ = 6) and different degrees of directionality. These spectra are from the set of observations collected in a directional wave tank by Onorato et al (2009). Spectrum A is very narrow in angle (corresponding to N = 840 in the cosN directional model). Spectrum B is initially wider in angle (corresponds to N = 24). Short-term evolution of both spectra (O(102) wave periods) has been studied numerically by Xiao et al (2013) using two other approaches (broad-band modified nonlinear Schrödinger equation and direct numerical simulation based on the high-order spectral method). We use these results to verify the initial stage of our DNS-ZE simulations. However, the advantage of the DNS-ZE method is that it allows to study long-term spectral evolution (up to O(104) periods), which was previously possible only with the KE. In the short-term evolution

  15. Spectral Skyline Separation: Extended Landmark Databases and Panoramic Imaging

    Directory of Open Access Journals (Sweden)

    Dario Differt

    2016-09-01

    Full Text Available Evidence from behavioral experiments suggests that insects use the skyline as a cue for visual navigation. However, changes of lighting conditions, over hours, days or possibly seasons, significantly affect the appearance of the sky and ground objects. One possible solution to this problem is to extract the “skyline” by an illumination-invariant classification of the environment into two classes, ground objects and sky. In a previous study (Insect models of illumination-invariant skyline extraction from UV (ultraviolet and green channels, we examined the idea of using two different color channels available for many insects (UV and green to perform this segmentation. We found out that for suburban scenes in temperate zones, where the skyline is dominated by trees and artificial objects like houses, a “local” UV segmentation with adaptive thresholds applied to individual images leads to the most reliable classification. Furthermore, a “global” segmentation with fixed thresholds (trained on an image dataset recorded over several days using UV-only information is only slightly worse compared to using both the UV and green channel. In this study, we address three issues: First, to enhance the limited range of environments covered by the dataset collected in the previous study, we gathered additional data samples of skylines consisting of minerals (stones, sand, earth as ground objects. We could show that also for mineral-rich environments, UV-only segmentation achieves a quality comparable to multi-spectral (UV and green segmentation. Second, we collected a wide variety of ground objects to examine their spectral characteristics under different lighting conditions. On the one hand, we found that the special case of diffusely-illuminated minerals increases the difficulty to reliably separate ground objects from the sky. On the other hand, the spectral characteristics of this collection of ground objects covers well with the data collected

  16. Feasibility study of a novel miniaturized spectral imaging system architecture in UAV surveillance

    Science.gov (United States)

    Liu, Shuyang; Zhou, Tao; Jia, Xiaodong; Cui, Hushan; Huang, Chengjun

    2016-01-01

    The spectral imaging technology is able to analysis the spectral and spatial geometric character of the target at the same time. To break through the limitation brought by the size, weight and cost of the traditional spectral imaging instrument, a miniaturized novel spectral imaging based on CMOS processing has been introduced in the market. This technology has enabled the possibility of applying spectral imaging in the UAV platform. In this paper, the relevant technology and the related possible applications have been presented to implement a quick, flexible and more detailed remote sensing system.

  17. Imaging of blood cells based on snapshot Hyper-Spectral Imaging systems

    Science.gov (United States)

    Robison, Christopher J.; Kolanko, Christopher; Bourlai, Thirimachos; Dawson, Jeremy M.

    2015-05-01

    Snapshot Hyper-Spectral imaging systems are capable of capturing several spectral bands simultaneously, offering coregistered images of a target. With appropriate optics, these systems are potentially able to image blood cells in vivo as they flow through a vessel, eliminating the need for a blood draw and sample staining. Our group has evaluated the capability of a commercial Snapshot Hyper-Spectral imaging system, the Arrow system from Rebellion Photonics, in differentiating between white and red blood cells on unstained blood smear slides. We evaluated the imaging capabilities of this hyperspectral camera; attached to a microscope at varying objective powers and illumination intensity. Hyperspectral data consisting of 25, 443x313 hyperspectral bands with ~3nm spacing were captured over the range of 419 to 494nm. Open-source hyper-spectral data cube analysis tools, used primarily in Geographic Information Systems (GIS) applications, indicate that white blood cells features are most prominent in the 428-442nm band for blood samples viewed under 20x and 50x magnification over a varying range of illumination intensities. These images could potentially be used in subsequent automated white blood cell segmentation and counting algorithms for performing in vivo white blood cell counting.

  18. MULTI-SPECTRAL AND HYPERSPECTRAL IMAGE FUSION USING 3-D WAVELET TRANSFORM

    Institute of Scientific and Technical Information of China (English)

    Zhang Yifan; He Mingyi

    2007-01-01

    Image fusion is performed between one band of multi-spectral image and two bands of hyperspectral image to produce fused image with the same spatial resolution as source multi-spectral image and the same spectral resolution as source hyperspectral image. According to the characteristics and 3-Dimensional (3-D) feature analysis of multi-spectral and hyperspectral image data volume, the new fusion approach using 3-D wavelet based method is proposed. This approach is composed of four major procedures: Spatial and spectral resampling, 3-D wavelet transform, wavelet coefficient integration and 3-D inverse wavelet transform. Especially, a novel method, Ratio Image Based Spectral Resampling (RIBSR) method, is proposed to accomplish data resampling in spectral domain by utilizing the property of ratio image. And a new fusion rule, Average and Substitution (A&S) rule, is employed as the fusion rule to accomplish wavelet coefficient integration. Experimental results illustrate that the fusion approach using 3-D wavelet transform can utilize both spatial and spectral characteristics of source images more adequately and produce fused image with higher quality and fewer artifacts than fusion approach using 2-D wavelet transform. It is also revealed that RIBSR method is capable of interpolating the missing data more effectively and correctly, and A&S rule can integrate coefficients of source images in 3-D wavelet domain to preserve both spatial and spectral features of source images more properly.

  19. Magnetic resonance imaging with nonlinear gradient fields signal encoding and image reconstruction

    CERN Document Server

    Schultz, Gerrit

    2013-01-01

    Within the past few decades magnetic resonance imaging has become one of the most important imaging modalities in medicine. For a reliable diagnosis of pathologies further technological improvements are of primary importance. This text deals with a radically new approach of image encoding: The fundamental principle of gradient linearity is challenged by investigating the possibilities of acquiring anatomical images with the help of nonlinear gradient fields. Besides a thorough theoretical analysis with a focus on signal encoding and image reconstruction, initial hardware implementations are tested using phantom as well as in-vivo measurements. Several applications are presented that give an impression about the implications that this technological advancement may have for future medical diagnostics.   Contents n  Image Reconstruction in MRI n  Nonlinear Gradient Encoding: PatLoc Imaging n  Presentation of Initial Hardware Designs n  Basics of Signal Encoding and Image Reconstruction in PatLoc Imaging n ...

  20. Adaptive Spectral Estimation Methods in Color Flow Imaging.

    Science.gov (United States)

    Karabiyik, Yucel; Ekroll, Ingvild Kinn; Eik-Nes, Sturla H; Avdal, Jorgen; Lovstakken, Lasse

    2016-11-01

    Clutter rejection for color flow imaging (CFI) remains a challenge due to either a limited amount of temporal samples available or nonstationary tissue clutter. This is particularly the case for interleaved CFI and B-mode acquisitions. Low velocity blood signal is attenuated along with the clutter due to the long transition band of the available clutter filters, causing regions of biased mean velocity estimates or signal dropouts. This paper investigates how adaptive spectral estimation methods, Capon and blood iterative adaptive approach (BIAA), can be used to estimate the mean velocity in CFI without prior clutter filtering. The approach is based on confining the clutter signal in a narrow spectral region around the zero Doppler frequency while keeping the spectral side lobes below the blood signal level, allowing for the clutter signal to be removed by thresholding in the frequency domain. The proposed methods are evaluated using computer simulations, flow phantom experiments, and in vivo recordings from the common carotid and jugular vein of healthy volunteers. Capon and BIAA methods could estimate low blood velocities, which are normally attenuated by polynomial regression filters, and may potentially give better estimation of mean velocities for CFI at a higher computational cost. The Capon method decreased the bias by 81% in the transition band of the used polynomial regression filter for small packet size ( N=8 ) and low SNR (5 dB). Flow phantom and in vivo results demonstrate that the Capon method can provide color flow images and flow profiles with lower variance and bias especially in the regions close to the artery walls.

  1. Modern Trends in Imaging X: Spectral Imaging in Preclinical Research and Clinical Pathology

    Directory of Open Access Journals (Sweden)

    Richard Levenson

    2012-01-01

    Full Text Available Spectral imaging methods are attracting increased interest from researchers and practitioners in basic science, pre-clinical and clinical arenas. A combination of better labeling reagents and better optics creates opportunities to detect and measure multiple parameters at the molecular and cellular level. These tools can provide valuable insights into the basic mechanisms of life, and yield diagnostic and prognostic information for clinical applications. There are many multispectral technologies available, each with its own advantages and limitations. This chapter will present an overview of the rationale for spectral imaging, and discuss the hardware, software and sample labeling strategies that can optimize its usefulness in clinical settings.

  2. Imaging of contact acoustic nonlinearity using synthetic aperture technique.

    Science.gov (United States)

    Yun, Dongseok; Kim, Jongbeom; Jhang, Kyung-Young

    2013-09-01

    The angle beam incidence and reflection technique for the evaluation of contact acoustic nonlinearity (CAN) at solid-solid contact interfaces (e.g., closed cracks) has recently been developed to overcome the disadvantage of accessing both the inner and outer surfaces of structures for attaching pulsing and receiving transducers in the through-transmission of normal incidence technique. This paper proposes a technique for B-mode imaging of CAN based on the above reflection technique, which uses the synthetic aperture focusing technique (SAFT) and short-time Fourier transform (STFT) to visualize the distribution of the CAN-induced second harmonic magnitude as well as the nonlinear parameter. In order to verify the usefulness of the proposed method, a solid-solid contact interface was tested and the change of the contact acoustic nonlinearity according to the increasing contact pressure was visualized in images of the second harmonic magnitude and the relative nonlinear parameter. The experimental results showed good agreement with the previously developed theory identifying the dependence of the scattered second harmonics on the contact pressure. This technique can be used for the detection and improvement of the sizing accuracy of closed cracks that are difficult to detect using the conventional linear ultrasonic technique.

  3. Nonlinear optical imaging characteristics in rat tail tendon

    Science.gov (United States)

    Liu, N. R.; Zhang, X. Z.; Qiu, Y. S.; Chen, R.

    2013-04-01

    The aim of this study was to examine the characteristics of skeletal muscle fibers in tail tendons, explore the content of intrinsic components at different depths and ascertain the optimum excitation wavelength, which will help to establish a relationship between diagnosis and therapy and the tendon injury. A multiphoton microscopic imaging system was used to achieve the images and spectra via an imaging mode and a Lambda mode, respectively. This work demonstrates that the skeletal muscle fibers of the tail tendon are in good order. Second harmonic generation (SHG) and two-photon excited fluorescence (TPEF) signals originating from certain intrinsic components are varied with depth, and the SHG/TPEF intensity ratios are varied at different excitation wavelengths. Below 800 nm is the optimum for cell TPEF, while above 800 nm is the optimum for SHG. With the development of imaging techniques, a nonlinear optical imaging system will be helpful to represent the functional behaviors of tissue related to tendon injury.

  4. Sparse Nonlinear Electromagnetic Imaging Accelerated With Projected Steepest Descent Algorithm

    KAUST Repository

    Desmal, Abdulla

    2017-04-03

    An efficient electromagnetic inversion scheme for imaging sparse 3-D domains is proposed. The scheme achieves its efficiency and accuracy by integrating two concepts. First, the nonlinear optimization problem is constrained using L₀ or L₁-norm of the solution as the penalty term to alleviate the ill-posedness of the inverse problem. The resulting Tikhonov minimization problem is solved using nonlinear Landweber iterations (NLW). Second, the efficiency of the NLW is significantly increased using a steepest descent algorithm. The algorithm uses a projection operator to enforce the sparsity constraint by thresholding the solution at every iteration. Thresholding level and iteration step are selected carefully to increase the efficiency without sacrificing the convergence of the algorithm. Numerical results demonstrate the efficiency and accuracy of the proposed imaging scheme in reconstructing sparse 3-D dielectric profiles.

  5. Content-based image retrieval of digitized histopathology in boosted spectrally embedded spaces

    Science.gov (United States)

    Sridhar, Akshay; Doyle, Scott; Madabhushi, Anant

    2015-01-01

    Context: Content-based image retrieval (CBIR) systems allow for retrieval of images from within a database that are similar in visual content to a query image. This is useful for digital pathology, where text-based descriptors alone might be inadequate to accurately describe image content. By representing images via a set of quantitative image descriptors, the similarity between a query image with respect to archived, annotated images in a database can be computed and the most similar images retrieved. Recently, non-linear dimensionality reduction methods have become popular for embedding high-dimensional data into a reduced-dimensional space while preserving local object adjacencies, thereby allowing for object similarity to be determined more accurately in the reduced-dimensional space. However, most dimensionality reduction methods implicitly assume, in computing the reduced-dimensional representation, that all features are equally important. Aims: In this paper we present boosted spectral embedding(BoSE), which utilizes a boosted distance metric to selectively weight individual features (based on training data) to subsequently map the data into a reduced-dimensional space. Settings and Design: BoSE is evaluated against spectral embedding (SE) (which employs equal feature weighting) in the context of CBIR of digitized prostate and breast cancer histopathology images. Materials and Methods: The following datasets, which were comprised of a total of 154 hematoxylin and eosin stained histopathology images, were used: (1) Prostate cancer histopathology (benign vs. malignant), (2) estrogen receptor (ER) + breast cancer histopathology (low vs. high grade), and (3) HER2+ breast cancer histopathology (low vs. high levels of lymphocytic infiltration). Statistical Analysis Used: We plotted and calculated the area under precision-recall curves (AUPRC) and calculated classification accuracy using the Random Forest classifier. Results: BoSE outperformed SE both in terms of

  6. Content-based image retrieval of digitized histopathology in boosted spectrally embedded spaces

    Directory of Open Access Journals (Sweden)

    Akshay Sridhar

    2015-01-01

    Full Text Available Context : Content-based image retrieval (CBIR systems allow for retrieval of images from within a database that are similar in visual content to a query image. This is useful for digital pathology, where text-based descriptors alone might be inadequate to accurately describe image content. By representing images via a set of quantitative image descriptors, the similarity between a query image with respect to archived, annotated images in a database can be computed and the most similar images retrieved. Recently, non-linear dimensionality reduction methods have become popular for embedding high-dimensional data into a reduced-dimensional space while preserving local object adjacencies, thereby allowing for object similarity to be determined more accurately in the reduced-dimensional space. However, most dimensionality reduction methods implicitly assume, in computing the reduced-dimensional representation, that all features are equally important. Aims : In this paper we present boosted spectral embedding (BoSE, which utilizes a boosted distance metric to selectively weight individual features (based on training data to subsequently map the data into a reduced-dimensional space. Settings and Design : BoSE is evaluated against spectral embedding (SE (which employs equal feature weighting in the context of CBIR of digitized prostate and breast cancer histopathology images. Materials and Methods : The following datasets, which were comprised of a total of 154 hematoxylin and eosin stained histopathology images, were used: (1 Prostate cancer histopathology (benign vs. malignant, (2 estrogen receptor (ER + breast cancer histopathology (low vs. high grade, and (3 HER2+ breast cancer histopathology (low vs. high levels of lymphocytic infiltration. Statistical Analysis Used : We plotted and calculated the area under precision-recall curves (AUPRC and calculated classification accuracy using the Random Forest classifier. Results : BoSE outperformed SE both

  7. Experimental demonstration of an adaptive architecture for direct spectral imaging classification.

    Science.gov (United States)

    Dunlop-Gray, Matthew; Poon, Phillip K; Golish, Dathon; Vera, Esteban; Gehm, Michael E

    2016-08-08

    Spectral imaging is a powerful tool for providing in situ material classification across a spatial scene. Typically, spectral imaging analyses are interested in classification, though often the classification is performed only after reconstruction of the spectral datacube. We present a computational spectral imaging system, the Adaptive Feature-Specific Spectral Imaging Classifier (AFSSI-C), which yields direct classification across the spatial scene without reconstruction of the source datacube. With a dual disperser architecture and a programmable spatial light modulator, the AFSSI-C measures specific projections of the spectral datacube which are generated by an adaptive Bayesian classification and feature design framework. We experimentally demonstrate multiple order-of-magnitude improvement of classification accuracy in low signal-to-noise (SNR) environments when compared to legacy spectral imaging systems.

  8. Miniature Compressive Ultra-spectral Imaging System Utilizing a Single Liquid Crystal Phase Retarder

    Science.gov (United States)

    August, Isaac; Oiknine, Yaniv; Abuleil, Marwan; Abdulhalim, Ibrahim; Stern, Adrian

    2016-03-01

    Spectroscopic imaging has been proved to be an effective tool for many applications in a variety of fields, such as biology, medicine, agriculture, remote sensing and industrial process inspection. However, due to the demand for high spectral and spatial resolution it became extremely challenging to design and implement such systems in a miniaturized and cost effective manner. Using a Compressive Sensing (CS) setup based on a single variable Liquid Crystal (LC) retarder and a sensor array, we present an innovative Miniature Ultra-Spectral Imaging (MUSI) system. The LC retarder acts as a compact wide band spectral modulator. Within the framework of CS, a sequence of spectrally modulated images is used to recover ultra-spectral image cubes. Using the presented compressive MUSI system, we demonstrate the reconstruction of gigapixel spatio-spectral image cubes from spectral scanning shots numbering an order of magnitude less than would be required using conventional systems.

  9. Comparison of spectral CT imaging methods based a photon-counting detector: Experimental study

    Science.gov (United States)

    Lee, Youngjin; Lee, Seungwan; Kim, Hee-Joung

    2016-04-01

    Photon-counting detectors allow spectral computed tomography (CT) imaging using energy-resolved information from a polychromatic X-ray spectrum. The spectral CT images based on the photon-counting detectors are dependent on the energy ranges defined by energy bins for image acquisition. In this study, K-edge and energy weighting imaging methods were experimentally implemented by using a spectral CT system with a cadmium zinc telluride (CZT)-based photon-counting detector. The spectral CT images were obtained by various energy bins and compared in terms of CNR improvement for investigating the effect of energy bins and the efficiency of the spectral CT imaging methods. The results showed that the spectral CT image quality was improved by using the particular energy bins, which were optimized for each spectral CT imaging method and target material. The CNR improvement was different for the spectral CT imaging methods and target materials. It can be concluded that an appropriate selection of imaging method for each target material and the optimization of energy bin can maximize the quality of spectral CT images.

  10. Comparison of spectral CT imaging methods based a photon-counting detector: Experimental study

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Youngjin [Department of Radiological Science, College of Health Science, Eulji University, 553 Sangseong-daero, Seongnam, Gyeonggi-do 461-713 (Korea, Republic of); Lee, Seungwan, E-mail: slee1@konyang.ac.kr [Department of Radiological Science, College of Medical Science, Konyang University, 158 Gwanjeodong-ro, Daejeon 302-812 (Korea, Republic of); Kim, Hee-Joung [Department of Radiological Science, College of Health Science, Yonsei University, 1 Yonseidae-gil, Wonju, Kangwon-do 220-710 (Korea, Republic of)

    2016-04-11

    Photon-counting detectors allow spectral computed tomography (CT) imaging using energy-resolved information from a polychromatic X-ray spectrum. The spectral CT images based on the photon-counting detectors are dependent on the energy ranges defined by energy bins for image acquisition. In this study, K-edge and energy weighting imaging methods were experimentally implemented by using a spectral CT system with a cadmium zinc telluride (CZT)-based photon-counting detector. The spectral CT images were obtained by various energy bins and compared in terms of CNR improvement for investigating the effect of energy bins and the efficiency of the spectral CT imaging methods. The results showed that the spectral CT image quality was improved by using the particular energy bins, which were optimized for each spectral CT imaging method and target material. The CNR improvement was different for the spectral CT imaging methods and target materials. It can be concluded that an appropriate selection of imaging method for each target material and the optimization of energy bin can maximize the quality of spectral CT images.

  11. Spectral imager based on Fabry-Perot interferometer for Aalto-1 nanosatellite

    Science.gov (United States)

    Mannila, Rami; Näsilä, Antti; Viherkanto, Kai; Holmlund, Christer; Näkki, Ismo; Saari, Heikki

    2013-09-01

    The Aalto-1 is a 3U-cubesat project coordinated by Aalto University. The satellite, Aalto-1, will be mainly built by students as project assignments and thesis works. The Aalto-1 is planned to launch on 2014. VTT Technical Research Centre of Finland is developing the main Earth observation payload, a miniaturized spectral imager unit, for the satellite. The spectral imager unit contains a spectral imager, a visible RGB-camera and control electronics of the cameras. Detailed design of the spectral imager unit has been completed and assembly of the spectral imager unit will be done in the autumn 2013. The spectral imager is based on a tunable Fabry-Perot interferometer (FPI) accompanied by an RGB CMOS image sensor. The FPI consists of two highly reflective surfaces separated by a tunable air gap and it is based on a piezo-actuated structure. The piezo-actuated FPI uses three piezo-actuators and is controlled in a closed capacitive feedback loop. The spectral resolution of the imager will be 8-15 nm at full width at half maximum and it will operate in the wavelength range 500-900 nm. Imaging resolution of the spectral imager is 1024x1024 pixels and the focal length of the optics is 32 mm and F-number is 3.4. Mass of the spectral imager unit is approximately 600 grams, and dimensions are 97 mm x 97 mm x 48 mm.

  12. Utilization of multiple frequencies in 3D nonlinear microwave imaging

    DEFF Research Database (Denmark)

    Jensen, Peter Damsgaard; Rubæk, Tonny; Mohr, Johan Jacob

    2012-01-01

    The use of multiple frequencies in a nonlinear microwave algorithm is considered. Using multiple frequencies allows for obtaining the improved resolution available at the higher frequencies while retaining the regularizing effects of the lower frequencies. However, a number of different challenges...... at lower frequencies are used as starting guesses for reconstructions at higher frequencies. The performance is illustrated using simulated 2-D data and data obtained with the 3-D DTU microwave imaging system....

  13. Nonlinear Fusion of Multispectral Citrus Fruit Image Data with Information Contents

    Science.gov (United States)

    Li, Peilin; Lee, Sang-Heon; Hsu, Hung-Yao; Park, Jae-Sam

    2017-01-01

    The main issue of vison-based automatic harvesting manipulators is the difficulty in the correct fruit identification in the images under natural lighting conditions. Mostly, the solution has been based on a linear combination of color components in the multispectral images. However, the results have not reached a satisfactory level. To overcome this issue, this paper proposes a robust nonlinear fusion method to augment the original color image with the synchronized near infrared image. The two images are fused with Daubechies wavelet transform (DWT) in a multiscale decomposition approach. With DWT, the background noises are reduced and the necessary image features are enhanced by fusing the color contrast of the color components and the homogeneity of the near infrared (NIR) component. The resulting fused color image is classified with a C-means algorithm for reconstruction. The performance of the proposed approach is evaluated with the statistical F measure in comparison to some existing methods using linear combinations of color components. The results show that the fusion of information in different spectral components has the advantage of enhancing the image quality, therefore improving the classification accuracy in citrus fruit identification in natural lighting conditions. PMID:28098797

  14. Color camera computed tomography imaging spectrometer for improved spatial-spectral image accuracy

    Science.gov (United States)

    Wilson, Daniel W. (Inventor); Bearman, Gregory H. (Inventor); Johnson, William R. (Inventor)

    2011-01-01

    Computed tomography imaging spectrometers ("CTIS"s) having color focal plane array detectors are provided. The color FPA detector may comprise a digital color camera including a digital image sensor, such as a Foveon X3.RTM. digital image sensor or a Bayer color filter mosaic. In another embodiment, the CTIS includes a pattern imposed either directly on the object scene being imaged or at the field stop aperture. The use of a color FPA detector and the pattern improves the accuracy of the captured spatial and spectral information.

  15. The Influence of Spectral Wavelength on the Quality of Pansharpened Image Simulated Using Hyperspectral Data

    Science.gov (United States)

    Matsuoka, M.

    2012-07-01

    Preservation of the spectral characteristics in multispectral images is important in the development of pansharpening methods because it affects the accuracy of subsequent applications, such as visual interpretation, land cover classification, and change detection. The combinations of the spectral properties (observation wavelength and width of spectral bands) of multispectral and panchromatic images affect both the spatial and spectral quality of pansharpened images. Therefore, the clarification of the relations between spectral bands and quality of pansharpened image is important for improving our understanding of pansharpening methods, and for developing better schemes for image fusion. This study investigated the influence of the spectral waveband of panchromatic images on the image quality of multispectral (MS) images using simulated images produced from hyperspectral data. Panchromatic images with different spectral band position and multispectral images with degraded spatial resolution were generated from airborne visible/infrared imaging spectrometer (AVIRIS) images and pansharpened using seven methods: additive wavelet intensity, additive wavelet principal component, generalized Laplacian pyramid with spectral distortion minimization, generalized intensity-huesaturation (GIHS) transform, GIHS adaptive, Gram-Schmidt spectral sharpening, and block-based synthetic variable ratio. The pansharpened near-infrared band was visually and statistically compared with the non-degraded image. Wide variation in quality was identified visually within and between methods depending on the spectral wavelengths of the panchromatic images. Quantitative evaluations using three frequently used indices, the correlation coefficient, erreur relative globale adimensionnelle de synthèse (ERGAS), and the Q index, showed the individual behaviors of the pansharpening methods in terms of the spectral similarity in panchromatic and near-infrared, though all methods had similar qualities

  16. Nonlinear optical signal processing for high-speed, spectrally efficient fiber optic systems and networks

    Science.gov (United States)

    Zhang, Bo

    The past decade has witnessed astounding boom in telecommunication network traffic. With the emergence of multimedia over Internet, the high-capacity optical transport systems have started to shift focus from the core network towards the end users. This trend leads to diverse optical networks with transparency and reconfigurability requirement. As single channel data rate continues to increase and channel spacing continues to shrink for high capacity, high spectral efficiency, the workload on conventional electronic signal processing elements in the router nodes continues to build up. Performing signal processing functions in the optical domain can potentially alleviate the speed bottleneck if the unique optical properties are efficiently leveraged to assist electronic processing methodologies. Ultra-high bandwidth capability along with the promise for multi-channel and format-transparent operation make optical signal processing an attractive technology which is expected to have great impact on future optical networks. For optical signal processing applications in fiber-optic network and systems, a laudable goal would be to explore the unique nonlinear optical processes in novel photonic devices. This dissertation investigates novel optical signal processing techniques through simulations and experimental demonstrations, analyzes limitations of these nonlinear processing elements and proposes techniques to enhance the system performance or designs for functional photonic modules. Two key signal-processing building blocks for future optical networks, namely slow-light-based tunable optical delay lines and SOA-based high-speed wavelength converters, are presented in the first part of the dissertation. Phase preserving and spectrally efficient slow light are experimentally demonstrated using advanced modulation formats. Functional and novel photonic modules, such as multi-channel synchronizer and variable-bit-rate optical time division multiplexer are designed and

  17. Nonlinear complexity and spectral analyses of heart rate variability in medicated and unmedicated patients with schizophrenia.

    Science.gov (United States)

    Mujica-Parodi, L R; Yeragani, Vikram; Malaspina, Dolores

    2005-01-01

    Heart rate variability (HRV) reflects functioning of the autonomic nervous system and possibly also regulation by the neural limbic system, abnormalities of which have both figured prominently in various etiological models of schizophrenia, particularly those that address patients' vulnerability to stress in connection to psychosis onset and exacerbation. This study provides data on cardiac functioning in a sample of schizophrenia patients that were either medication free or on atypical antipsychotics, as well as cardiac data on matched healthy controls. We included a medication-free group to investigate whether abnormalities in HRV previously reported in the literature and associated with atypical antipsychotics were solely the effect of medications or whether they might be a feature of the illness (or psychosis) itself. We collected 24-hour ECGs on 19 patients and 24 controls. Of the patients, 9 were medication free and 10 were on atypical antipsychotics. All subject groups were matched for age and gender. Patient groups showed equivalent symptom severity and type, as well as duration of illness. We analyzed the data using nonlinear complexity (symbolic dynamic) HRV analyses as well as standard and relative spectral analyses. For the medication-free patients as compared to the healthy controls, our data show decreased R-R intervals during sleep, and abnormal suppression of all frequency ranges, but particularly the low frequency range, which persisted even after adjusting the spectral data for the mean R-R interval. This effect was exacerbated for patients on atypical antipsychotics. Likewise, nonlinear complexity analysis showed significantly impaired HRV for medication-free patients that was exacerbated in the patients on atypical antipsychotics. Altogether, the data suggest a pattern of significantly decreased cardiac vagal function of patients with schizophrenia as compared to healthy controls, apart from and beyond any differences due to medication side

  18. Spectral imaging of multi-color chromogenic dyes in pathological specimens.

    NARCIS (Netherlands)

    Macville, M.V.E.; Laak, J.A.W.M. van der; Speel, E.J.; Katzir, N.; Garini, Y.; Soenksen, D.; McNamara, G.; Wilde, P.C.M. de; Hanselaar, A.G.J.M.; Hopman, A.H.N.; Ried, T.

    2001-01-01

    We have investigated the use of spectral imaging for multi-color analysis of permanent cytochemical dyes and enzyme precipitates on cytopathological specimens. Spectral imaging is based on Fourier-transform spectroscopy and digital imaging. A pixel-by-pixel spectrum-based color classification is pre

  19. Terahertz detectors for long wavelength multi-spectral imaging.

    Energy Technology Data Exchange (ETDEWEB)

    Lyo, Sungkwun Kenneth; Wanke, Michael Clement; Reno, John Louis; Shaner, Eric Arthur; Grine, Albert D.

    2007-10-01

    The purpose of this work was to develop a wavelength tunable detector for Terahertz spectroscopy and imaging. Our approach was to utilize plasmons in the channel of a specially designed field-effect transistor called the grating-gate detector. Grating-gate detectors exhibit narrow-linewidth, broad spectral tunability through application of a gate bias, and no angular dependence in their photoresponse. As such, if suitable sensitivity can be attained, they are viable candidates for Terahertz multi-spectral focal plane arrays. When this work began, grating-gate gate detectors, while having many promising characteristics, had a noise-equivalent power (NEP) of only 10{sup -5} W/{radical}Hz. Over the duration of this project, we have obtained a true NEP of 10{sup -8} W/{radical}Hz and a scaled NEP of 10{sup -9}W/{radical}Hz. The ultimate goal for these detectors is to reach a NEP in the 10{sup -9{yields}-10}W/{radical}Hz range; we have not yet seen a roadblock to continued improvement.

  20. Pigment identification in pictorial layers by HyperSpectral Imaging

    Science.gov (United States)

    Capobianco, Giuseppe; Bonifazi, Giuseppe; Prestileo, Fernanda; Serranti, Silvia

    2014-05-01

    The use of Hyper-Spectral Imaging (HSI) as a diagnostic tool in the field of cultural heritage is of great interest presenting high potentialities. This analysis, in fact, is non-destructive, non-invasive and portable. Furthermore, the possibility to couple hyperspectral data with chemometric techniques allows getting qualitative and/or quantitative information on the nature and physical-chemical characteristics of the investigated materials. A study was carried out to explore the possibilities offered by this approach to identify pigments in paintings. More in detail, six pigments have been selected and they have been then mixed with four different binders and applied to a wood support. The resulting reference samples were acquired by HSI in the SWIR wavelength range (1000-2500 nm). Data were processed adopting a chemometric approach based on the PLS Toolbox (Eigenvector Research, Inc.) running inside Matlab® (The Mathworks, Inc.). The aim of the study was to verify, according to the information acquired in the investigated wavelength region, the correlation existing between collected spectral signatures and sample characteristics related to the different selected pigments and binders. Results were very good showing as correlations exist. New scenarios can thus be envisaged for analysis, characterization, conservation and restoration of paintings, considering that the developed approach allows to obtain, just "in one shot", information, not only on the type of pigment, but also on the utilized binder and support.

  1. ANALYSIS OF CAMOUFLAGE COVER SPECTRAL CHARACTERISTICS BY IMAGING SPECTROMETER

    Directory of Open Access Journals (Sweden)

    A. Y. Kouznetsov

    2016-03-01

    Full Text Available Subject of Research.The paper deals with the problems of detection and identification of objects in hyperspectral imagery. The possibility of object type determination by statistical methods is demonstrated. The possibility of spectral image application for its data type identification is considered. Method. Researching was done by means of videospectral equipment for objects detection at "Fregat" substrate. The postprocessing of hyperspectral information was done with the use of math model of pattern recognition system. The vegetation indexes TCHVI (Three-Channel Vegetation Index and NDVI (Normalized Difference Vegetation Index were applied for quality control of object recognition. Neumann-Pearson criterion was offered as a tool for determination of objects differences. Main Results. We have carried out analysis of the spectral characteristics of summer-typecamouflage cover (Germany. We have calculated the density distribution of vegetation indexes. We have obtained statistical characteristics needed for creation of mathematical model for pattern recognition system. We have shown the applicability of vegetation indices for detection of summer camouflage cover on averdure background. We have presented mathematical model of object recognition based on Neumann-Pearson criterion. Practical Relevance. The results may be useful for specialists in the field of hyperspectral data processing for surface state monitoring.

  2. Label-free imaging through nonlinear optical signals

    Directory of Open Access Journals (Sweden)

    Ling Tong

    2011-06-01

    Full Text Available Strong intrinsic nonlinear optical (NLO signals not only make nanostructures promising agents for bio-imaging, but also advance NLO microscopy for the study of interactions between nanomaterials and live cells. Single beam modalities such as multiphoton luminescence, second harmonic generation, and third harmonic generation provide a simple way to probe many types of nanostructures. As for more advanced modalities, photothermal heterodyne imaging provides improved detection sensitivity for smaller objects, and transient absorption microscopy provides structural information to distinguish metal from semiconducting carbon nanotubes, and eumelanin from pheomelanin. The four-wave mixing signal achieves chemical selectivity in the presence of either vibrational or electronic resonance, as used in coherent Raman scattering imaging of molecules and in electronically resonance enhanced four-wave mixing imaging of nanostructures.

  3. Iterative reconstruction of images from incomplete spectral data

    Science.gov (United States)

    Rhebergen, Jan B.; van den Berg, Peter M.; Habashy, Tarek M.

    1997-06-01

    In various branches of engineering and science, one is confronted with measurements resulting in incomplete spectral data. The problem of the reconstruction of an image from such a data set can be formulated in terms of an integral equation of the first kind. Consequently, this equation can be converted into an equivalent integral equation of the second kind which can be solved by a Neumann-type iterative method. It is shown that this Neumann expansion is an error-reducing method and that it is equivalent to the Papoulis - Gerchberg algorithm for band-limited signal extrapolation. The integral equation can also be solved by employing a conjugate gradient iterative scheme. Again, convergence of this scheme is demonstrated. Finally a number of illustrative numerical examples are presented and discussed.

  4. Unsupervised learning of cone spectral classes from natural images.

    Directory of Open Access Journals (Sweden)

    Noah C Benson

    2014-06-01

    Full Text Available The first step in the evolution of primate trichromatic color vision was the expression of a third cone class not present in ancestral mammals. This observation motivates a fundamental question about the evolution of any sensory system: how is it possible to detect and exploit the presence of a novel sensory class? We explore this question in the context of primate color vision. We present an unsupervised learning algorithm capable of both detecting the number of spectral cone classes in a retinal mosaic and learning the class of each cone using the inter-cone correlations obtained in response to natural image input. The algorithm's ability to classify cones is in broad agreement with experimental evidence about functional color vision for a wide range of mosaic parameters, including those characterizing dichromacy, typical trichromacy, anomalous trichromacy, and possible tetrachromacy.

  5. Unsupervised learning of cone spectral classes from natural images.

    Science.gov (United States)

    Benson, Noah C; Manning, Jeremy R; Brainard, David H

    2014-06-01

    The first step in the evolution of primate trichromatic color vision was the expression of a third cone class not present in ancestral mammals. This observation motivates a fundamental question about the evolution of any sensory system: how is it possible to detect and exploit the presence of a novel sensory class? We explore this question in the context of primate color vision. We present an unsupervised learning algorithm capable of both detecting the number of spectral cone classes in a retinal mosaic and learning the class of each cone using the inter-cone correlations obtained in response to natural image input. The algorithm's ability to classify cones is in broad agreement with experimental evidence about functional color vision for a wide range of mosaic parameters, including those characterizing dichromacy, typical trichromacy, anomalous trichromacy, and possible tetrachromacy.

  6. Method for detection and imaging over a broad spectral range

    Science.gov (United States)

    Yefremenko, Volodymyr; Gordiyenko, Eduard; Pishko, legal representative, Olga; Novosad, Valentyn; Pishko, deceased; Vitalii

    2007-09-25

    A method of controlling the coordinate sensitivity in a superconducting microbolometer employs localized light, heating or magnetic field effects to form normal or mixed state regions on a superconducting film and to control the spatial location. Electron beam lithography and wet chemical etching were applied as pattern transfer processes in epitaxial Y--Ba--Cu--O films. Two different sensor designs were tested: (i) a 3 millimeter long and 40 micrometer wide stripe and (ii) a 1.25 millimeters long, and 50 micron wide meandering-like structure. Scanning the laser beam along the stripe leads to physical displacement of the sensitive area, and, therefore, may be used as a basis for imaging over a broad spectral range. Forming the superconducting film as a meandering structure provides the equivalent of a two-dimensional detector array. Advantages of this approach are simplicity of detector fabrication, and simplicity of the read-out process requiring only two electrical terminals.

  7. Color image encryption based on Coupled Nonlinear Chaotic Map

    Energy Technology Data Exchange (ETDEWEB)

    Mazloom, Sahar [Faculty of Electrical, Computer and IT Engineering, Qazvin Islamic Azad University, Qazvin (Iran, Islamic Republic of)], E-mail: sahar.mazloom@gmail.com; Eftekhari-Moghadam, Amir Masud [Faculty of Electrical, Computer and IT Engineering, Qazvin Islamic Azad University, Qazvin (Iran, Islamic Republic of)], E-mail: eftekhari@qazviniau.ac.ir

    2009-11-15

    Image encryption is somehow different from text encryption due to some inherent features of image such as bulk data capacity and high correlation among pixels, which are generally difficult to handle by conventional methods. The desirable cryptographic properties of the chaotic maps such as sensitivity to initial conditions and random-like behavior have attracted the attention of cryptographers to develop new encryption algorithms. Therefore, recent researches of image encryption algorithms have been increasingly based on chaotic systems, though the drawbacks of small key space and weak security in one-dimensional chaotic cryptosystems are obvious. This paper proposes a Coupled Nonlinear Chaotic Map, called CNCM, and a novel chaos-based image encryption algorithm to encrypt color images by using CNCM. The chaotic cryptography technique which used in this paper is a symmetric key cryptography with a stream cipher structure. In order to increase the security of the proposed algorithm, 240 bit-long secret key is used to generate the initial conditions and parameters of the chaotic map by making some algebraic transformations to the key. These transformations as well as the nonlinearity and coupling structure of the CNCM have enhanced the cryptosystem security. For getting higher security and higher complexity, the current paper employs the image size and color components to cryptosystem, thereby significantly increasing the resistance to known/chosen-plaintext attacks. The results of several experimental, statistical analysis and key sensitivity tests show that the proposed image encryption scheme provides an efficient and secure way for real-time image encryption and transmission.

  8. Designing Non-linear Frequency Modulated Signals For Medical Ultrasound Imaging

    DEFF Research Database (Denmark)

    Gran, Fredrik; Jensen, Jørgen Arendt

    2006-01-01

    is tested experimentally using the RASMUS ultrasound system with a 7 MHz linear array transducer. Synthetic transmit aperture ultrasound imaging is applied to acquire data. The proposed design method was compared to a linear FM signal. Due to more efficient spectral usage, a gain in SNR of 4.3plusmn1.2 d......In this paper a new method for designing non-linear frequency modulated (NLFM) waveforms for ultrasound imaging is proposed. The objective is to control the amplitude spectrum of the designed waveform and still keep a constant transmit amplitude, so that the transmitted energy is maximized...... in the transducer can be decreased. Secondly, by choosing an appropriate amplitude spectrum, no additional temporal tapering has to be applied to the matched filter to achieve sufficient range sidelobe suppression. Proper design results in waveforms with a range sidelobe level beyond -80 dB. The design method...

  9. [Full-field and automatic methodology of spectral calibration for PGP imaging spectrometer].

    Science.gov (United States)

    Sun, Ci; Bayanheshig; Cui, Ji-cheng; Pan, Ming-zhong; Li, Xiao-tian; Tang, Yu-guo

    2014-08-01

    In order to analyze spectral data quantitatively which is obtained by prism-grating-prism imaging spectrometer, spectral calibration is required in order to determine spectral characteristics of PGP imaging spectrometer, such as the center wavelength of every spectral channel, spectral resolution and spectral bending. A spectral calibration system of full field based on collimated monochromatic light method is designed. Spherical mirror is used to provide collimated light, and a freely sliding and rotating folding mirror is adopted to change the angle of incident light in order to realize full field and automatic calibration of imaging spectrometer. Experiments of spectral calibration have been done for PGP imaging spectrometer to obtain parameters of spectral performance, and accuracy analysis combined with the structural features of the entire spectral calibration system have been done. Analysis results indicate that spectral calibration accuracy of the calibration system reaches 0.1 nm, and the bandwidth accuracy reaches 1.3%. The calibration system has merits of small size, better commonality, high precision and so on, and because of adopting the control of automation, the additional errors which are caused by human are avoided. The calibration system can be used for spectral calibration of other imaging spectrometers whose structures are similar to PGP.

  10. Extremely Nonlinear Optics Using Shaped Pulses Spectrally Broadened in an Argon- or Sulfur Hexafluoride-Filled Hollow-Core Fiber

    Directory of Open Access Journals (Sweden)

    Andreas Hoffmann

    2015-11-01

    Full Text Available In this contribution we present a comparison of the performance of spectrally broadened ultrashort pulses using a hollow-core fiber either filled with argon or sulfur hexafluoride (SF6 for demanding pulse-shaping experiments. The benefits of both gases for pulse-shaping are studied in the highly nonlinear process of high-harmonic generation. In this setup, temporally shaping the driving laser pulse leads to spectrally shaping of the output extreme ultraviolet (XUV spectrum, where total yield and spectral selectivity in the XUV are the targets of the optimization approach. The effect of using sulfur hexafluoride for pulse-shaping the XUV yield can be doubled compared to pulse compression and pulse-shaping using argon and the spectral range for selective optimization of a single harmonic can be extended. The obtained results are of interest for extending the range of ultrafast science applications drawing on tailored XUV fields.

  11. Adaptive hyperspectral imaging with a MEMS-based full-frame programmable spectral filter

    Science.gov (United States)

    Graff, David L.; Love, Steven P.

    2014-05-01

    Rapidly programmable spatial light modulation devices based on MEMS technology have opened an exciting new arena in spectral imaging: rapidly reprogrammable, high spectral resolution, multi-band spectral filters that enable hyperspectral processing directly in the optical hardware of an imaging sensor. Implemented as a multiplexing spectral selector, a digital micro-mirror device (DMD) can independently choose or reject dozens or hundreds of spectral bands and present them simultaneously to an imaging sensor, forming a complete 2D image. The result is a high-speed, highresolution, programmable spectral filter that gives the user complete control over the spectral content of the image formed at the sensor. This technology enables a wide variety of rapidly reprogrammable operational capabilities within the same sensor including broadband, color, false color, multispectral, hyperspectral and target specific, matched filter imaging. Of particular interest is the ability to implement target-specific hyperspectral matched filters directly into the optical train of the sensor, producing an image highlighting a target within a spectrally cluttered scene in real time without further processing. By performing the hyperspectral image processing at the sensor, such a system can operate with high performance, greatly reduced data volume, and at a fraction of the cost of traditional push broom hyperspectral instruments. Examples of color, false color and target-specific matched-filter images recorded with our visible-spectrum prototype will be displayed, and extensions to other spectral regions will be discussed.

  12. Nonlinear Interferometric Vibrational Imaging (NIVI) with Novel Optical Sources

    Science.gov (United States)

    Boppart, Stephen A.; King, Matthew D.; Liu, Yuan; Tu, Haohua; Gruebele, Martin

    Optical imaging is essential in medicine and in fundamental studies of biological systems. Although many existing imaging modalities can supply valuable information, not all are capable of label-free imaging with high-contrast and molecular specificity. The application of molecular or nanoparticle contrast agents may adversely influence the biological system under investigation. These substances also present ongoing concerns over toxicity or particle clearance, which must be properly addressed before their approval for in vivo human imaging. Hence there is an increasing appreciation for label-free imaging techniques. It is of primary importance to develop imaging techniques that can indiscriminately identify and quantify biochemical compositions to high degrees of sensitivity and specificity through only the intrinsic optical response of endogenous molecular species. The development and use of nonlinear interferometric vibrational imaging, which is based on the interferometric detection of optical signals from coherent anti-Stokes Raman scattering (CARS), along with novel optical sources, offers the potential for label-free molecular imaging.

  13. Non-linear image scanning microscopy (Conference Presentation)

    Science.gov (United States)

    Gregor, Ingo; Ros, Robert; Enderlein, Jörg

    2017-02-01

    Nowadays, multiphoton microscopy can be considered as a routine method for the observation of living cells, organs, up to whole organisms. Second-harmonics generation (SHG) imaging has evolved to a powerful qualitative and label-free method for studying fibrillar structures, like collagen networks. However, examples of super-resolution non-linear microscopy are rare. So far, such approaches require complex setups and advanced synchronization of scanning elements limiting the image acquisition rates. We describe theory and realization of a super-resolution image scanning microscope [1, 2] using two-photon excited fluorescence as well as second-harmonic generation. It requires only minor modifications compared to a classical two-photon laser-scanning microscope and allows image acquisition at the high frame rates of a resonant galvo-scanner. We achieve excellent sensitivity and high frame-rate in combination with two-times improved lateral resolution. We applied this method to fixed cells, collagen hydrogels, as well as living fly embryos. Further, we proofed the excellent image quality of our setup for deep tissue imaging. 1. Müller C.B. and Enderlein J. (2010) Image scanning microscopy. Phys. Rev. Lett. 104(19), 198101. 2. Sheppard C.J.R. (1988) Super-resolution in confocal imaging. Optik (Stuttg) 80 53-54.

  14. Design and implementation of non-linear image processing functions for CMOS image sensor

    Science.gov (United States)

    Musa, Purnawarman; Sudiro, Sunny A.; Wibowo, Eri P.; Harmanto, Suryadi; Paindavoine, Michel

    2012-11-01

    Today, solid state image sensors are used in many applications like in mobile phones, video surveillance systems, embedded medical imaging and industrial vision systems. These image sensors require the integration in the focal plane (or near the focal plane) of complex image processing algorithms. Such devices must meet the constraints related to the quality of acquired images, speed and performance of embedded processing, as well as low power consumption. To achieve these objectives, low-level analog processing allows extracting the useful information in the scene directly. For example, edge detection step followed by a local maxima extraction will facilitate the high-level processing like objects pattern recognition in a visual scene. Our goal was to design an intelligent image sensor prototype achieving high-speed image acquisition and non-linear image processing (like local minima and maxima calculations). For this purpose, we present in this article the design and test of a 64×64 pixels image sensor built in a standard CMOS Technology 0.35 μm including non-linear image processing. The architecture of our sensor, named nLiRIC (non-Linear Rapid Image Capture), is based on the implementation of an analog Minima/Maxima Unit. This MMU calculates the minimum and maximum values (non-linear functions), in real time, in a 2×2 pixels neighbourhood. Each MMU needs 52 transistors and the pitch of one pixel is 40×40 mu m. The total area of the 64×64 pixels is 12.5mm2. Our tests have shown the validity of the main functions of our new image sensor like fast image acquisition (10K frames per second), minima/maxima calculations in less then one ms.

  15. Review of spectral imaging technology in biomedical engineering: achievements and challenges.

    Science.gov (United States)

    Li, Qingli; He, Xiaofu; Wang, Yiting; Liu, Hongying; Xu, Dongrong; Guo, Fangmin

    2013-10-01

    Spectral imaging is a technology that integrates conventional imaging and spectroscopy to get both spatial and spectral information from an object. Although this technology was originally developed for remote sensing, it has been extended to the biomedical engineering field as a powerful analytical tool for biological and biomedical research. This review introduces the basics of spectral imaging, imaging methods, current equipment, and recent advances in biomedical applications. The performance and analytical capabilities of spectral imaging systems for biological and biomedical imaging are discussed. In particular, the current achievements and limitations of this technology in biomedical engineering are presented. The benefits and development trends of biomedical spectral imaging are highlighted to provide the reader with an insight into the current technological advances and its potential for biomedical research.

  16. Effects of Heat Transfer and Nonlinear Slip on the Steady Flow of Couette Fluid by Means of Chebyshev Spectral Method

    Science.gov (United States)

    Ellahi, Rahmat; Wang, Xinil; Hameed, Muhammad

    2014-02-01

    This article is concerned with the study of heat transfer and nonlinear slip effects on the Couette flow of a third-grade fluid. Numerical solutions are obtained by solving nonlinear differential equations using the higher-order Chebyshev spectral method. The results for no slip and no thermal slip become special cases of this study. Moreover, the results for Poiseuille flow can be obtained as a special case from the generalized Couette flow analysis by setting the plate velocity to zero. Graphical results for involved pertinent parameters are sketched and examined.

  17. Non-linear Imaging using an Experimental Synthetic Aperture Real Time Ultrasound Scanner

    DEFF Research Database (Denmark)

    Rasmussen, Joachim; Du, Yigang; Jensen, Jørgen Arendt

    2011-01-01

    This paper presents the first non-linear B-mode image of a wire phantom using pulse inversion attained via an experimental synthetic aperture real-time ultrasound scanner (SARUS). The purpose of this study is to implement and validate non-linear imaging on SARUS for the further development of new...... non-linear techniques. This study presents non-linear and linear B-mode images attained via SARUS and an existing ultrasound system as well as a Field II simulation. The non-linear image shows an improved spatial resolution and lower full width half max and -20 dB resolution values compared to linear...

  18. Retinal Imaging of Infants on Spectral Domain Optical Coherence Tomography

    Directory of Open Access Journals (Sweden)

    Anand Vinekar

    2015-01-01

    Full Text Available Spectral domain coherence tomography (SD OCT has become an important tool in the management of pediatric retinal diseases. It is a noncontact imaging device that provides detailed assessment of the microanatomy and pathology of the infant retina with a short acquisition time allowing office examination without the requirement of anesthesia. Our understanding of the development and maturation of the infant fovea has been enhanced by SD OCT allowing an in vivo assessment that correlates with histopathology. This has helped us understand the critical correlation of foveal development with visual potential in the first year of life and beyond. In this review, we summarize the recent literature on the clinical applications of SD OCT in studying the pathoanatomy of the infant macula, its ability to detect subclinical features, and its correlation with disease and vision. Retinopathy of prematurity and macular edema have been discussed in detail. The review also summarizes the current status of SD OCT in other infant retinal conditions, imaging the optic nerve, the choroid, and the retinal nerve fibre in infants and children, and suggests future areas of research.

  19. Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2014-05-04

    Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.

  20. Preconditioned Inexact Newton for Nonlinear Sparse Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2014-01-06

    Newton-type algorithms have been extensively studied in nonlinear microwave imaging due to their quadratic convergence rate and ability to recover images with high contrast values. In the past, Newton methods have been implemented in conjunction with smoothness promoting optimization/regularization schemes. However, this type of regularization schemes are known to perform poorly when applied in imagining domains with sparse content or sharp variations. In this work, an inexact Newton algorithm is formulated and implemented in conjunction with a linear sparse optimization scheme. A novel preconditioning technique is proposed to increase the convergence rate of the optimization problem. Numerical results demonstrate that the proposed framework produces sharper and more accurate images when applied in sparse/sparsified domains.

  1. Augmenting Forest Stand Parameters using Landsat TM Spectral Images

    Science.gov (United States)

    Reuveni, Y.; Dahan, E.; Anker, Y.; Sprintsin, M.

    2015-12-01

    Forest stand parameters, such as diameter at breast height (DBH), tree height (H), or volume per hectare (V), are imperative for forest resources assessment. Traditional inventory of forest stand parameters, usually based on fieldwork, is often difficult, time-consuming, and expensive, to conduct in large areas. Therefore, estimating forest stand parameters in large areas using traditional inventory approach augmented by satellites data has a significant implication for sustainable forest management and natural resources efficiency. However, obtaining suitable satellite image data for such purpose is a challenging task mainly because of insignificant knowledge between the forest stand parameters and satellite spectral response relationships. Here, we present the use of Landsat Thematic Mapper (TM) spectral responses data for augmenting forest stand parameter obtained from fieldwork at the Lahav Forest, in the Israeli Northern Negev. A new algorithm was developed in order to use all eight TM band when calculating the linear combination which correlates the most to each one of the forest stand parameters. Each linear combination is obtained first for local area inside the entire studied grid and is then fitted using a simple linear polynomial curve to the known forest stand parameter. Once the relationship between the two is characterized by a linear polynomial equation, the TM linear combination local area data is translated to the same equivalent area of the chosen forest stand parameter. At last, we interpolate the entire TM grid using a higher order polynomial fit applied to all the augmented local area combined together to attain full coverage of the desired forest stand parameter.

  2. Semi-supervised segmentation of multispectral remote sensing image based on spectral clustering

    Science.gov (United States)

    Zhang, Xiangrong; Wang, Ting; Jiao, Licheng; Yang, Chun

    2009-10-01

    In this paper, a new multi-spectral remote sensing image segmentation method based on multi-parameter semi-supervised spectral clustering (STS3C) is proposed. Two types of instance-level constraints: must-link and cannot-link are incorporated into spectral cluster to construct semi-supervised spectral clustering in which the self-tuning parameter is applied to avoid the selection of the scaling parameter. Further, when STS3C is applied to multi-spectral remote sensing image segmentation, the uniform sampling technique combined with nearest neighbor rule is used to reduce the computation complexity. Segmentation results show that STS3C outperforms the semi-supervised spectral clustering with fixed parameter and the well-known clustering methods including k-means and FCM in multi-spectral remote sensing image segmentation.

  3. Software defined multi-spectral imaging for Arctic sensor networks

    Science.gov (United States)

    Siewert, Sam; Angoth, Vivek; Krishnamurthy, Ramnarayan; Mani, Karthikeyan; Mock, Kenrick; Singh, Surjith B.; Srivistava, Saurav; Wagner, Chris; Claus, Ryan; Vis, Matthew Demi

    2016-05-01

    Availability of off-the-shelf infrared sensors combined with high definition visible cameras has made possible the construction of a Software Defined Multi-Spectral Imager (SDMSI) combining long-wave, near-infrared and visible imaging. The SDMSI requires a real-time embedded processor to fuse images and to create real-time depth maps for opportunistic uplink in sensor networks. Researchers at Embry Riddle Aeronautical University working with University of Alaska Anchorage at the Arctic Domain Awareness Center and the University of Colorado Boulder have built several versions of a low-cost drop-in-place SDMSI to test alternatives for power efficient image fusion. The SDMSI is intended for use in field applications including marine security, search and rescue operations and environmental surveys in the Arctic region. Based on Arctic marine sensor network mission goals, the team has designed the SDMSI to include features to rank images based on saliency and to provide on camera fusion and depth mapping. A major challenge has been the design of the camera computing system to operate within a 10 to 20 Watt power budget. This paper presents a power analysis of three options: 1) multi-core, 2) field programmable gate array with multi-core, and 3) graphics processing units with multi-core. For each test, power consumed for common fusion workloads has been measured at a range of frame rates and resolutions. Detailed analyses from our power efficiency comparison for workloads specific to stereo depth mapping and sensor fusion are summarized. Preliminary mission feasibility results from testing with off-the-shelf long-wave infrared and visible cameras in Alaska and Arizona are also summarized to demonstrate the value of the SDMSI for applications such as ice tracking, ocean color, soil moisture, animal and marine vessel detection and tracking. The goal is to select the most power efficient solution for the SDMSI for use on UAVs (Unoccupied Aerial Vehicles) and other drop

  4. Methods for Enhancing Geological Structures in Spectral Spatial Difference-Based on Remote-Sensing Image

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    @@In this paper, some image processing methods such as directional template (mask) matching enhancement, pseudocolor or false color enhancement, K-L transform enhancement are used to enhance a geological structure, one of important ore-controlling factors, shown in the remote-sensing images.This geological structure is regarded as image anomaly in the remote-sensing image, since considerable differences, based on the spatial spectral distribution pattern, in gray values (spectral), color tones and texture, are always present between the geological structure and background. Therefore,the enhancement of the geological structure in the remotesensing image is that of the spectral spatial difference.

  5. An Improved Variational Method for Hyperspectral Image Pansharpening with the Constraint of Spectral Difference Minimization

    Science.gov (United States)

    Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.

    2017-09-01

    Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.

  6. High-speed molecular spectral imaging of tissue with stimulated Raman scattering

    Science.gov (United States)

    Ozeki, Yasuyuki; Umemura, Wataru; Otsuka, Yoichi; Satoh, Shuya; Hashimoto, Hiroyuki; Sumimura, Kazuhiko; Nishizawa, Norihiko; Fukui, Kiichi; Itoh, Kazuyoshi

    2012-12-01

    To date, medical imaging of tissues has largely relied on time-consuming staining processes, and there is a need for rapid, label-free imaging techniques. Stimulated Raman scattering microscopy offers a three-dimensional, real-time imaging capability with chemical specificity. However, it can be difficult to differentiate between several constituents in tissues because their spectral characteristics can overlap. Furthermore, imaging speeds in previous multispectral stimulated Raman scattering imaging techniques were limited. Here, we demonstrate label-free imaging of tissues by 30 frames/s stimulated Raman scattering microscopy with frame-by-frame wavelength tunability. To produce multicolour images showing different constituents, spectral images were processed by modified independent component analysis, which can extract small differences in spectral features. We present various imaging modalities such as two-dimensional spectral imaging of rat liver, two-colour three-dimensional imaging of a vessel in rat liver, spectral imaging of several sections of intestinal villi in mouse, and in vivo spectral imaging of mouse ear skin.

  7. Phasor analysis of multiphoton spectral images distinguishes autofluorescence components of in vivo human skin.

    Science.gov (United States)

    Fereidouni, Farzad; Bader, Arjen N; Colonna, Anne; Gerritsen, Hans C

    2014-08-01

    Skin contains many autofluorescent components that can be studied using spectral imaging. We employed a spectral phasor method to analyse two photon excited autofluorescence and second harmonic generation images of in vivo human skin. This method allows segmentation of images based on spectral features. Various structures in the skin could be distinguished, including Stratum Corneum, epidermal cells and dermis. The spectral phasor analysis allowed investigation of their fluorescence composition and identification of signals from NADH, keratin, FAD, melanin, collagen and elastin. Interestingly, two populations of epidermal cells could be distinguished with different melanin content.

  8. Application of multivariate statistical analysis to STEM X-ray spectral images: interfacial analysis in microelectronics.

    Science.gov (United States)

    Kotula, Paul G; Keenan, Michael R

    2006-12-01

    Multivariate statistical analysis methods have been applied to scanning transmission electron microscopy (STEM) energy-dispersive X-ray spectral images. The particular application of the multivariate curve resolution (MCR) technique provides a high spectral contrast view of the raw spectral image. The power of this approach is demonstrated with a microelectronics failure analysis. Specifically, an unexpected component describing a chemical contaminant was found, as well as a component consistent with a foil thickness change associated with the focused ion beam specimen preparation process. The MCR solution is compared with a conventional analysis of the same spectral image data set.

  9. Nonlinear filtering for character recognition in low quality document images

    Science.gov (United States)

    Diaz-Escobar, Julia; Kober, Vitaly

    2014-09-01

    Optical character recognition in scanned printed documents is a well-studied task, where the captured conditions like sheet position, illumination, contrast and resolution are controlled. Nowadays, it is more practical to use mobile devices for document capture than a scanner. So as a consequence, the quality of document images is often poor owing to presence of geometric distortions, nonhomogeneous illumination, low resolution, etc. In this work we propose to use multiple adaptive nonlinear composite filters for detection and classification of characters. Computer simulation results obtained with the proposed system are presented and discussed.

  10. Stimulated Raman hyperspectral imaging based on spectral filtering of broadband fiber laser pulses.

    Science.gov (United States)

    Ozeki, Yasuyuki; Umemura, Wataru; Sumimura, Kazuhiko; Nishizawa, Norihiko; Fukui, Kiichi; Itoh, Kazuyoshi

    2012-02-01

    We demonstrate a technique of hyperspectral imaging in stimulated Raman scattering (SRS) microscopy using a tunable optical filter, whose transmission wavelength can be varied quickly by a galvanometer mirror. Experimentally, broadband Yb fiber laser pulses are synchronized with picosecond Ti:sapphire pulses, and then spectrally filtered out by the filter. After amplification by fiber amplifiers, we obtain narrowband pulses with a spectral width of 225 cm(-1). By using these pulses, we accomplish SRS imaging of polymer beads with spectral information.

  11. Frequency up-conversion based single photon, mid-IR spectral imaging with 20% quantum efficiency

    DEFF Research Database (Denmark)

    Tidemand-Lichtenberg, Peter; Dam, Jeppe Seidelin; Pedersen, Christian

    Spectral imaging of mid-infrared (mid-IR) light is emerging as a promising technology since important chemical compounds display unique and strong mid-IR spectral fingerprints. We demonstrate for detection a novel method including a field deployable imaging system with single photon sensitivity...

  12. Spectral quasi-linearisation method for nonlinear thermal convection flow of a micropolar fluid under convective boundary condition

    Science.gov (United States)

    RamReddy, Ch.; Pradeepa, T.

    2016-09-01

    The significance of nonlinear temperaturedependent density relation and convective boundary condition on natural convection flow of an incompressible micropolar fluid with homogeneous-heterogeneous reactions is analyzed. In spite of the complicated nonlinear structure of the present setup and to allow all the essential features, the representation of similarity transformations for the system of non-dimensional fluid flow equations is attained through Lie group transformations and hence the governing similarity equations are worked out by a numerical approach known as spectral quasi-linearization method. It is noticed that in the presence of the nonlinear convection parameter enhance the velocity, species concentration, heat transfer rate, skin friction, but decreases the temperature and wall couple stress.

  13. [Application of data fusion of microscopic spectral imaging in reservoir characterization].

    Science.gov (United States)

    Li, Jing; Zha, Ming; Guo, Yuan-Ling; Chen, Yong

    2011-10-01

    In recent years, spectral imaging technique has been applied widely in mineralogy and petrology. The technique combines the spectral technique with imaging technique. The samples can be analyzed and recognized both in spectra and space by using the technique. However, the problem is how to acquire the needful information from a large number of data of spectral imaging, and how to enhance the needful information. In the present paper, the experimental data were processed by using the technique of data fusion of microscopic spectral imaging. The space distribution map of chemical composition and physical parameters of samples were obtained. The result showed that the distribution of different hydrocarbon in the reservoirs, pore connectivity, etc. were revealed well. The technique of data fusion of microscopic spectral imaging provided a new method for reservoir characterization.

  14. Radiometric and spectral calibrations of the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) using principle component analysis

    Science.gov (United States)

    Tian, Jialin; Smith, William L.; Gazarik, Michael J.

    2008-10-01

    The ultimate remote sensing benefits of the high resolution Infrared radiance spectrometers will be realized with their geostationary satellite implementation in the form of imaging spectrometers. This will enable dynamic features of the atmosphere's thermodynamic fields and pollutant and greenhouse gas constituents to be observed for revolutionary improvements in weather forecasts and more accurate air quality and climate predictions. As an important step toward realizing this application objective, the Geostationary Imaging Fourier Transform Spectrometer (GIFTS) Engineering Demonstration Unit (EDU) was successfully developed under the NASA New Millennium Program, 2000-2006. The GIFTS-EDU instrument employs three focal plane arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw GIFTS interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. The radiometric calibration is achieved using internal blackbody calibration references at ambient (260 K) and hot (286 K) temperatures. The absolute radiometric performance of the instrument is affected by several factors including the FPA off-axis effect, detector/readout electronics induced nonlinearity distortions, and fore-optics offsets. The GIFTS-EDU, being the very first imaging spectrometer to use ultra-high speed electronics to readout its large area format focal plane array detectors, operating at wavelengths as large as 15 microns, possessed non-linearity's not easily removable in the initial calibration process. In this paper, we introduce a refined calibration technique that utilizes Principle Component (PC) analysis to compensate for instrument distortions and artifacts remaining after the initial radiometric calibration process, thus, further enhance the absolute calibration accuracy. This method is

  15. Imaging the anisotropic nonlinear Meissner effect in unconventional superconductors

    Energy Technology Data Exchange (ETDEWEB)

    Zhuravel, Alexander P. [B. Verkin Institute for Low Temperature Physics and Engineering, National Academy of Sciences of Ukraine, Kharkov (Ukraine); Ghamsari, Behnood G.; Kurter, Cihan; Abrahams, John [CNAM, Physics Department, University of Maryland, College Park, MD (United States); Jung, Philipp; Lukashenko, Alexander; Ustinov, Alexey V. [Physikalisches Institut and DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology, Karlsruhe (Germany); Remillard, Stephen [Physics Department, Hope College, Holland, MI (United States); Anlage, Steven M. [CNAM, Physics Department, University of Maryland, College Park, MD (United States); Physikalisches Institut and DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology, Karlsruhe (Germany)

    2013-07-01

    We present measurements on the anisotropic nonlinear Meissner effect (aNLME). Using a laser scanning microscope we have directly imaged this effect in a self-resonant spiral patterned from a thin film of the d{sub x{sup 2}-y{sup 2}} superconductor YBa{sub 2}Cu{sub 3}O{sub 7-δ}. The spiral is excited at one of its resonant frequencies while a focused laser spot is scanned across its surface. The local illumination by the laser gives rise to a detectable change in the resonant properties. At low temperatures, the aNLME causes a direction dependent contribution to the critical current density. This makes it possible to image the directions of nodes and anti-nodes of the superconducting order parameter and the contribution of Andreev bound states associated with them. These two contributions to the photoresponse can be distinguished by their temperature dependence, which is consistent with theoretical predictions.

  16. Quantitative method to assess caries via fluorescence imaging from the perspective of autofluorescence spectral analysis

    Science.gov (United States)

    Chen, Q. G.; Zhu, H. H.; Xu, Y.; Lin, B.; Chen, H.

    2015-08-01

    A quantitative method to discriminate caries lesions for a fluorescence imaging system is proposed in this paper. The autofluorescence spectral investigation of 39 teeth samples classified by the International Caries Detection and Assessment System levels was performed at 405 nm excitation. The major differences in the different caries lesions focused on the relative spectral intensity range of 565-750 nm. The spectral parameter, defined as the ratio of wavebands at 565-750 nm to the whole spectral range, was calculated. The image component ratio R/(G + B) of color components was statistically computed by considering the spectral parameters (e.g. autofluorescence, optical filter, and spectral sensitivity) in our fluorescence color imaging system. Results showed that the spectral parameter and image component ratio presented a linear relation. Therefore, the image component ratio was graded as 1.62 to quantitatively classify sound, early decay, established decay, and severe decay tissues, respectively. Finally, the fluorescence images of caries were experimentally obtained, and the corresponding image component ratio distribution was compared with the classification result. A method to determine the numerical grades of caries using a fluorescence imaging system was proposed. This method can be applied to similar imaging systems.

  17. Short-wave infrared (SWIR) spectral imager based on Fabry-Perot interferometer for remote sensing

    Science.gov (United States)

    Mannila, Rami; Holmlund, Christer; Ojanen, Harri J.; Näsilä, Antti; Saari, Heikki

    2014-10-01

    VTT Technical Research Centre of Finland has developed a spectral imager for short-wave infrared (SWIR) wavelength range. The spectral imager is based on a tunable Fabry-Perot interferometer (FPI) accompanied by a commercial InGaAs Camera. The FPI consists of two dielectric coated mirrors separated by a tunable air gap. Tuning of the air gap tunes also transmitted wavelength and therefore FPI acts as a tunable band bass filter. The FPI is piezo-actuated and it uses three piezo-actuators in a closed capacitive feedback loop for air gap tuning. The FPI has multiple order transmission bands, which limit free spectral range. Therefore spectral imager contains two FPI in a stack, to make possible to cover spectral range of 1000 - 1700 nm. However, in the first tests imager was used with one FPI and spectral range was limited to 1100-1600 nm. The spectral resolution of the imager is approximately 15 nm (FWHM). Field of view (FOV) across the flight direction is 30 deg. Imaging resolution of the spectral imager is 256 x 320 pixels. The focal length of the optics is 12 mm and F-number is 3.2. This imager was tested in summer 2014 in an unmanned aerial vehicle (UAV) and therefore a size and a mass of the imager were critical. Total mass of the imager is approximately 1200 grams. In test campaign the spectral imager will be used for forest and agricultural imaging. In future, because results of the UAV test flights are promising, this technology can be applied to satellite applications also.

  18. Spectral images browsing using principal component analysis and set partitioning in hierarchical tree

    Science.gov (United States)

    Ma, Long; Zhao, Deping

    2011-12-01

    Spectral imaging technology have been used mostly in remote sensing, but have recently been extended to new area requiring high fidelity color reproductions like telemedicine, e-commerce, etc. These spectral imaging systems are important because they offer improved color reproduction quality not only for a standard observer under a particular illuminantion, but for any other individual exhibiting normal color vision capability under another illuminantion. A possibility for browsing of the archives is needed. In this paper, the authors present a new spectral image browsing architecture. The architecture for browsing is expressed as follow: (1) The spectral domain of the spectral image is reduced with the PCA transform. As a result of the PCA transform the eigenvectors and the eigenimages are obtained. (2) We quantize the eigenimages with the original bit depth of spectral image (e.g. if spectral image is originally 8bit, then quantize eigenimage to 8bit), and use 32bit floating numbers for the eigenvectors. (3) The first eigenimage is lossless compressed by JPEG-LS, the other eigenimages were lossy compressed by wavelet based SPIHT algorithm. For experimental evalution, the following measures were used. We used PSNR as the measurement for spectral accuracy. And for the evaluation of color reproducibility, ΔE was used.here standard D65 was used as a light source. To test the proposed method, we used FOREST and CORAL spectral image databases contrain 12 and 10 spectral images, respectively. The images were acquired in the range of 403-696nm. The size of the images were 128*128, the number of bands was 40 and the resolution was 8 bits per sample. Our experiments show the proposed compression method is suitable for browsing, i.e., for visual purpose.

  19. Learning nonlinear statistical regularities in natural images by modeling the outer product of image intensities.

    Science.gov (United States)

    Qi, Peng; Hu, Xiaolin

    2014-04-01

    It is well known that there exist nonlinear statistical regularities in natural images. Existing approaches for capturing such regularities always model the image intensities by assuming a parameterized distribution for the intensities and learn the parameters. In the letter, we propose to model the outer product of image intensities by assuming a gaussian distribution for it. A two-layer structure is presented, where the first layer is nonlinear and the second layer is linear. Trained on natural images, the first-layer bases resemble the receptive fields of simple cells in the primary visual cortex (V1), while the second-layer units exhibit some properties of the complex cells in V1, including phase invariance and masking effect. The model can be seen as an approximation of the covariance model proposed in Karklin and Lewicki (2009) but has more robust and efficient learning algorithms.

  20. Nonlinear temporal filtering of time-resolved digital particle image velocimetry data

    Energy Technology Data Exchange (ETDEWEB)

    Fore, L.B.; Tung, A.T.; Buchanan, J.R.; Welch, J.W. [Bechtel Bettis Inc., West Mifflin, PA (United States)

    2005-07-01

    Nonlinear filtering methods have been developed to identify and replace outlying data points in velocity time series obtained with time-resolved digital particle image velocimetry (PIV) of the flow around a surface-mounted cube at a Reynolds number of 20,000. Nuances associated with the spectral computation of the cross-correlation are highlighted, including the requirement of zero-padding an image interrogation area to eliminate the circular components of the cross-correlation. Three nonlinear filtering methods for the replacement of outliers are applied to the velocity time series sampled at 1,000 Hz: a median filter, a decision-based Hampel filter, and a PIV-specific Hampel filter. The particular benefit of the PIV-specific Hampel filter is that it allows the retention of actual measured data, sometimes derived from alternate peaks in the cross-correlation function, while still providing for the removal of outliers when a consistent, nonoutlying measurement is not available. (orig.)

  1. Compressive spectral polarization imaging by a pixelized polarizer and colored patterned detector.

    Science.gov (United States)

    Fu, Chen; Arguello, Henry; Sadler, Brian M; Arce, Gonzalo R

    2015-11-01

    A compressive spectral and polarization imager based on a pixelized polarizer and colored patterned detector is presented. The proposed imager captures several dispersed compressive projections with spectral and polarization coding. Stokes parameter images at several wavelengths are reconstructed directly from 2D projections. Employing a pixelized polarizer and colored patterned detector enables compressive sensing over spatial, spectral, and polarization domains, reducing the total number of measurements. Compressive sensing codes are specially designed to enhance the peak signal-to-noise ratio in the reconstructed images. Experiments validate the architecture and reconstruction algorithms.

  2. Importance of the texture features in a query from a spectral image database

    Science.gov (United States)

    Kohonen, Oili; Hauta-Kasari, Markku

    2006-01-01

    A new, semantically meaningful technique for querying the images from a spectral image database is proposed. The technique is based on the use of both color- and texture features. The color features are calculated from spectral images by using the Self-Organizing Map (SOM) when methods of Gray Level Co-occurrence Matrix (GLCM) and Local Binary Pattern (LBP) are used for constructing the texture features. The importance of texture features in a querying is seen in experimental results, which are given by using a real spectral image database. Also the differences between the results gained by the use of co-occurrence matrix and LBP are introduced.

  3. The characteristic analysis of spectral image for cabbage leaves damaged by diamondback moth pests

    Science.gov (United States)

    Lin, Li-bo; Li, Hong-ning; Cao, Peng-fei; Qin, Feng; Yang, Shu-ming; Feng, Jie

    2015-02-01

    Cabbage growth and health diagnosis are important parts for cabbage fine planting, spectral imaging technology with the advantages of obtaining spectrum and space information of the target at the same time, which has become a research hotspot at home and abroad. The experiment measures the reflection spectrum at different stages using liquid crystal tunable filter (LCTF) and monochromatic CMOS camera composed of spectral imaging system for cabbage leaves damaged by diamondback moth pests, and analyzes its feature bands and the change of spectral parameters. The study shows that the feature bands of cabbage leaves damaged by diamondback moth pests have a tendency to blue light direction, the red edge towards blue shift, and red valley raising in spectral characteristic parameters, which have a good indication in diagnosing the extent of cabbage damaged by pests. Therefore, it has a unique advantage of monitoring the cabbage leaves damaged by diamondback moth pests by combinating feature bands and spectral characteristic parameters in spectral imaging technology.

  4. Airborne hyperspectral imaging in the visible-to-mid wave infrared spectral range by fusing three spectral sensors

    Science.gov (United States)

    Jakovels, Dainis; Filipovs, Jevgenijs; Erinš, Gatis; Taskovs, Juris

    2014-10-01

    Airborne hyperspectral imaging is widely used for remote sensing of environment. The choice of spectral region usually depends on the availability and cost of the sensor. Visible-to-near infrared (400-1100 nm) spectral range corresponds to spectral sensitivity of relatively cheap Si detectors therefore it is the most commonly used. The implementation of shortwave infrared (1100-3000 nm) requires more expensive solutions, but can provide valuable information about the composition of the substance. Mid wave infrared (3000-8000 nm) is rarely used for civilian applications, but it provides information on the thermal emission of materials. The fusion of different sensors allows spectral analysis of a wider spectral range combining and improving already existing algorithms for the analysis of chemical content and classification. Here we introduce our Airborne Surveillance and Environmental Monitoring System (ARSENAL) that was developed by fusing seven sensors. The first test results from the fusion of three hyperspectral imaging sensors in the visible-to-mid wave infrared (365-5000 nm) are demonstrated. Principal component analysis (PCA) is applied to test correlation between principal components (PCs) and common vegetation indices.

  5. Nonlinear Imaging of Microbubble Contrast Agent Using the Volterra Filter: In Vivo Results.

    Science.gov (United States)

    Du, Juan; Liu, Dalong; Ebbini, Emad S

    2016-12-01

    A nonlinear filtering approach to imaging the dynamics of microbubble ultrasound contrast agents (UCAs) in microvessels is presented. The approach is based on the adaptive third-order Volterra filter (TVF), which separates the linear, quadratic, and cubic components from beamformed pulse-echo ultrasound data. The TVF captures polynomial nonlinearities utilizing the full spectral components of the echo data and not from prespecified bands, e.g., second or third harmonics. This allows for imaging using broadband pulse transmission to preserve the axial resolution and the SNR. In this paper, we present the results from imaging the UCA activity in a 200- [Formula: see text] cellulose tube embedded in a tissue-mimicking phantom using a linear array diagnostic probe. The contrast enhancement was quantified by computing the contrast-to-tissue ratio (CTR) for the different imaging components, i.e., B-mode, pulse inversion (PI), and the TVF components. The temporal mean and standard deviation of the CTR values were computed for all frames in a given data set. Quadratic and cubic images, referred to as QB-mode and CB-mode, produced higher mean CTR values than B-mode, which showed improved sensitivity. Compared with PI, they produced similar or higher mean CTR values with greater spatial specificity. We also report in vivo results from imaging UCA activity in an implanted LNCaP tumor with heterogeneous perfusion. The temporal means and standard deviations of the echogenicity were evaluated in small regions with different perfusion levels in the presence and absence of UCA. The in vivo measurements behaved consistently with the corresponding calculations obtained under microflow conditions in vitro. Specifically, the nonlinear VF components produced larger increases in the temporal mean and standard deviation values compared with B-mode in regions with low to relatively high perfusion. These results showed that polynomial filters such as the TVF can provide an important tool

  6. Pulse-driven non-linear Alfvén waves and their role in the spectral line broadening

    Science.gov (United States)

    Chmielewski, P.; Srivastava, A. K.; Murawski, K.; Musielak, Z. E.

    2013-01-01

    We study the impulsively generated non-linear Alfvén waves in the solar atmosphere and describe their most likely role in the observed non-thermal broadening of some spectral lines in solar coronal holes. We solve numerically the time-dependent magnetohydrodynamic equations to find temporal signatures of large-amplitude Alfvén waves in the solar atmosphere model of open and expanding magnetic field configuration, with a realistic temperature distribution. We calculate the temporally and spatially averaged, instantaneous transversal velocity of non-linear Alfvén waves at different heights of the model atmosphere and estimate its contribution to the unresolved non-thermal motions caused by the waves. We find that the pulse-driven non-linear Alfvén waves with the amplitude Av = 50 km s- 1 are the most likely candidates for the non-thermal broadening of Si viii λ1445.75 Å line profiles in the polar coronal hole as reported by Banerjee et al. We also demonstrate that the Alfvén waves driven by comparatively smaller velocity pulse with amplitude Av = 25 km s- 1 may contribute to the spectral line width of the same line at various heights in coronal hole broadening. We conclude that the non-linear Alfvén waves excited impulsively in the lower solar atmosphere may be responsible for the observed spectral line broadening in polar coronal holes. This is an important result as it allows us to conclude that such large amplitude and pulse-driven Alfvén waves may indeed exist in solar coronal holes. The existence of these waves may impart the required momentum to accelerate the solar wind.

  7. Growth, spectral, linear and nonlinear optical characteristics of an efficient semiorganic acentric crystal: L-valinium L-valine chloride

    Energy Technology Data Exchange (ETDEWEB)

    Nageshwari, M.; Jayaprakash, P.; Kumari, C. Rathika Thaya [PG & Research Department of Physics, Arignar Anna Govt. Arts College, Cheyyar 604407, Tamil Nadu (India); Vinitha, G. [Department of Physics, School of Advanced Sciences, VIT Chennai, 600127 Tamil Nadu (India); Caroline, M. Lydia, E-mail: lydiacaroline2006@yahoo.co.in [PG & Research Department of Physics, Arignar Anna Govt. Arts College, Cheyyar 604407, Tamil Nadu (India)

    2017-04-15

    An efficient nonlinear optical semiorganic material L-valinium L-valine chloride (LVVCl) was synthesized and grown-up by means of slow evaporation process. Single crystal XRD evince that LVVCl corresponds to monoclinic system having acentric space group P2{sub 1}. The diverse functional groups existing in LVVCl were discovered with FTIR spectral investigation. The UV-Visible and photoluminescence spectrum discloses the optical and electronic properties respectively for the grown crystal. Several optical properties specifically extinction coefficient, reflectance, linear refractive index, electrical and optical conductivity were also determined. The SEM analysis was also carried out and it portrayed the surface morphology of LVVCl. The calculated value of laser damage threshold was 2.59 GW/cm{sup 2}. The mechanical and dielectric property of LVVCl was investigated employing microhardness and dielectric studies. The second and third order nonlinear optical characteristics of LVVCl was characterized utilizing Kurtz Perry and Z scan technique respectively clearly suggest its suitability in the domain of optics and photonics. - Graphical abstract: Good quality transparent single crystals of L-valinium L-valine chloride single crystal was grown by slow evaporation technique. The grown crystals were analyzed using different instrumentation methods to check its usefulness for the device fabrication. The determination of nonlinear refractive index (n{sub 2}), absorption coefficient (β) and third order nonlinear susceptibility was determined by Z scan technique, highlighted that LVVCl can serve as a promising candidate for opto electronic and nonlinear optical applications.

  8. Laser-induced fluorescence imaging of subsurface tissue structures with a volume holographic spatial-spectral imaging system.

    Science.gov (United States)

    Luo, Yuan; Gelsinger-Austin, Paul J; Watson, Jonathan M; Barbastathis, George; Barton, Jennifer K; Kostuk, Raymond K

    2008-09-15

    A three-dimensional imaging system incorporating multiplexed holographic gratings to visualize fluorescence tissue structures is presented. Holographic gratings formed in volume recording materials such as a phenanthrenquinone poly(methyl methacrylate) photopolymer have narrowband angular and spectral transmittance filtering properties that enable obtaining spatial-spectral information within an object. We demonstrate this imaging system's ability to obtain multiple depth-resolved fluorescence images simultaneously.

  9. Molecular probes for nonlinear optical imaging of biological membranes

    Science.gov (United States)

    Blanchard-Desce, Mireille H.; Ventelon, Lionel; Charier, Sandrine; Moreaux, Laurent; Mertz, Jerome

    2001-12-01

    Second-harmonic generation (SHG) and two-photon excited fluorescence (TPEF) are nonlinear optical (NLO) phenomena that scale with excitation intensity squared, and hence give rise to an intrinsic 3-dimensional resolution when used in microscopic imaging. TPEF microscopy has gained widespread popularity in the biology community whereas SHG microscopy promises to be a powerful tool because of its sensitivity to local asymmetry. We have implemented an approach toward the design of NLO-probes specifically adapted for SHG and/or TPEF imaging of biological membranes. Our strategy is based on the design of nanoscale amphiphilic NLO-phores. We have prepared symmetrical bolaamphiphilic fluorophores combining very high two-photon absorption (TPA) cross-sections in the visible red region and affinity for cellular membranes. Their incorporation and orientation in lipid membranes can be monitored via TPEF anisotropy. We have also prepared amphiphilic push-pull chromophores exhibiting both large TPA cross-sections and very large first hyperpolarizabilities in the near-IR region. These NLO-probes have proved to be particularly useful for imaging of biological membranes by simultaneous SHG and TPEF microscopy and offer attractive prospects for real-time imaging of fundamental biological processes such as adhesion, fusion or reporting of membrane potentials.

  10. SAR image segmentation with entropy ranking based adaptive semi-supervised spectral clustering

    Science.gov (United States)

    Zhang, Xiangrong; Yang, Jie; Hou, Biao; Jiao, Licheng

    2010-10-01

    Spectral clustering has become one of the most popular modern clustering algorithms in recent years. In this paper, a new algorithm named entropy ranking based adaptive semi-supervised spectral clustering for SAR image segmentation is proposed. We focus not only on finding a suitable scaling parameter but also determining automatically the cluster number with the entropy ranking theory. Also, two kinds of constrains must-link and cannot-link based semi-supervised spectral clustering is applied to gain better segmentation results. Experimental results on SAR images show that the proposed method outperforms other spectral clustering algorithms.

  11. Near-Infrared Hyper-spectral Image Analysis of Astaxanthin Concentration in Fish Feed Coating

    DEFF Research Database (Denmark)

    Ljungqvist, Martin Georg; Ersbøll, Bjarne Kjær; Kobayashi, K.;

    2012-01-01

    The aim of this study was to investigate the possibility of predicting concentration levels of synthetic astaxanthin coating of aquaculture feed pellets by hyper-spectral image analysis in the near infra-red (NIR) range and optical filter design. The imaging devices used were a Videometer...... for prediction of the concentration level. The results show that it is possible to predict the level of synthetic astaxanthin coating using either hyper-spectral imaging or three bandpass filters (BPF)....

  12. Exploring infrared neural stimulation with multimodal nonlinear imaging (Conference Presentation)

    Science.gov (United States)

    Adams, Wilson R.; Mahadevan-Jansen, Anita

    2017-02-01

    Infrared neural stimulation (INS) provides optical control of neural excitability using near to mid-infrared (mid-IR) light, which allows for spatially selective, artifact-free excitation without the introduction of exogenous agents or genetic modification. Although neural excitability is mediated by a transient temperature increase due to water absorption of IR energy, the molecular nature of IR excitability in neural tissue remains unknown. Current research suggests that transient changes in local tissue temperature give rise to a myriad of cellular responses that have been individually attributed to IR mediated excitability. To further elucidate the underlying biophysical mechanisms, we have begun work towards employing a novel multimodal nonlinear imaging platform to probe the molecular underpinnings of INS. Our imaging system performs coherent anti-Stokes Raman scattering (CARS), stimulated Raman scattering (SRS), two-photon excitation fluorescence (TPEF), second-harmonic generation (SHG) and thermal imaging into a single platform that allows for unprecedented co-registration of thermal and biochemical information in real-time. Here, we present our work leveraging CARS and SRS in acute thalamocortical brain slice preparations. We observe the evolution of lipid and protein-specific Raman bands during INS and electrically evoked activity in real-time. Combined with two-photon fluorescence and second harmonic generation, we offer insight to cellular metabolism and membrane dynamics during INS. Thermal imaging allows for the coregistration of acquired biochemical information with temperature information. Our work previews the versatility and capabilities of coherent Raman imaging combined with multiphoton imaging to observe biophysical phenomena for neuroscience applications.

  13. Detecting Changes Between Optical Images of Different Spatial and Spectral Resolutions: a Fusion-Based Approach

    CERN Document Server

    Ferraris, Vinicius; Wei, Qi; Chabert, Marie

    2016-01-01

    Change detection is one of the most challenging issues when analyzing remotely sensed images. Comparing several multi-date images acquired through the same kind of sensor is the most common scenario. Conversely, designing robust, flexible and scalable algorithms for change detection becomes even more challenging when the images have been acquired by two different kinds of sensors. This situation arises in case of emergency under critical constraints. This paper presents, to the best of authors' knowledge, the first strategy to deal with optical images characterized by dissimilar spatial and spectral resolutions. Typical considered scenarios include change detection between panchromatic or multispectral and hyperspectral images. The proposed strategy consists of a 3-step procedure: i) inferring a high spatial and spectral resolution image by fusion of the two observed images characterized one by a low spatial resolution and the other by a low spectral resolution, ii) predicting two images with respectively the...

  14. ENSO and its modulations on annual and multidecadal timescales revealed by Nonlinear Laplacian Spectral Analysis

    Science.gov (United States)

    Giannakis, D.; Slawinska, J. M.

    2016-12-01

    The variability of the Indo-Pacific Ocean on interannual to multidecadal timescales is investigated in a millennial control run of CCSM4 and in observations using a recently introduced technique called Nonlinear Laplacian Spectral Analysis (NLSA). Through this technique, drawbacks associated with ad hoc pre-filtering of the input data are avoided, enabling recovery of low-frequency and intermittent modes not accessible previously via classical approaches. Here, a multiscale hierarchy of modes is identified for Indo-Pacific SST and numerous linkages between these patterns are revealed. On interannual timescales, a mode with spatiotemporal pattern corresponding to the fundamental component of ENSO emerges, along with modulations of the annual cycle by ENSO in agreement with ENSO combination mode theory. In spatiotemporal reconstructions, these patterns capture the seasonal southward migration of SST and zonal wind anomalies associated with termination of El Niño and La Niña events. Notably, this family of modes explains a significant portion of SST variance in Eastern Indian Ocean regions employed in the definition of Indian Ocean dipole (IOD) indices, suggesting that it should be useful for understanding the linkage of these indices with ENSO and the interaction of the Indian and Pacific Oceans. In model data, we find that the ENSO and ENSO combination modes are modulated on multidecadal timescales by a mode predominantly active in the western tropical Pacific - we call this mode West Pacific Multidecadal Oscillation (WPMO). Despite the relatively low variance explained by this mode, its dynamical role appears to be significant as it has clear sign-dependent modulating relationships with the interannual modes carrying most of the variance. In particular, cold WPMO events are associated with anomalous Central Pacific westerlies favoring stronger ENSO events, while warm WPMO events suppress ENSO activity. Moreover, the WPMO has significant climatic impacts as

  15. Blind Image Deblurring Driven by Nonlinear Processing in the Edge Domain

    Directory of Open Access Journals (Sweden)

    Stefania Colonnese

    2004-12-01

    Full Text Available This work addresses the problem of blind image deblurring, that is, of recovering an original image observed through one or more unknown linear channels and corrupted by additive noise. We resort to an iterative algorithm, belonging to the class of Bussgang algorithms, based on alternating a linear and a nonlinear image estimation stage. In detail, we investigate the design of a novel nonlinear processing acting on the Radon transform of the image edges. This choice is motivated by the fact that the Radon transform of the image edges well describes the structural image features and the effect of blur, thus simplifying the nonlinearity design. The effect of the nonlinear processing is to thin the blurred image edges and to drive the overall blind restoration algorithm to a sharp, focused image. The performance of the algorithm is assessed by experimental results pertaining to restoration of blurred natural images.

  16. [Influence of human body target's spectral characteristics on visual range of low light level image intensifiers].

    Science.gov (United States)

    Zhang, Jun-Ju; Yang, Wen-Bin; Xu, Hui; Liu, Lei; Tao, Yuan-Yaun

    2013-11-01

    To study the effect of different human target's spectral reflective characteristic on low light level (LLL) image intensifier's distance, based on the spectral characteristics of the night-sky radiation and the spectral reflective coefficients of common clothes, we established a equation of human body target's spectral reflective distribution, and analyzed the spectral reflective characteristics of different human targets wearing the clothes of different color and different material, and from the actual detection equation of LLL image intensifier distance, discussed the detection capability of LLL image intensifier for different human target. The study shows that the effect of different human target's spectral reflective characteristic on LLL image intensifier distance is mainly reflected in the average reflectivity rho(-) and the initial contrast of the target and the background C0. Reflective coefficient and spectral reflection intensity of cotton clothes are higher than polyester clothes, and detection capability of LLL image intensifier is stronger for the human target wearing cotton clothes. Experimental results show that the LLL image intensifiers have longer visual ranges for targets who wear cotton clothes than targets who wear same color but polyester clothes, and have longer visual ranges for targets who wear light-colored clothes than targets who wear dark-colored clothes. And in the full moon illumination conditions, LLL image intensifiers are more sensitive to the clothes' material.

  17. Compact multispectral fluorescence imaging system with spectral multiplexed volume holographic grating

    Science.gov (United States)

    Lv, Yanlu; Cai, Chuangjian; Bai, Jing; Luo, Jianwen

    2016-12-01

    Traditional spectral imaging systems mainly rely on spatial scanning or spectral scanning methods to acquire spatial and spectral features. The acquisition is time-consuming and cannot fully satisfy the need of monitoring dynamic phenomenon and observing different structures of the specimen simultaneously. To overcome these barriers, we develop a video-rate simultaneous multispectral imaging system built with a spectral multiplexed volume holographic grating (VHG) and few optical components. Four spectral multiplexed volume holograms optimized for four discrete spectral bands (centered at 488 nm, 530 nm, 590 nm and 620 nm) are recorded into an 8×12 mm photo-thermal refractive glass. The diffraction efficiencies of all the holograms within the multiplexed VHG are greater than 80%. With the high throughout multiplexed VHG, the system can work with both reflection and fluorescence modes and allow simultaneous acquisition of spectral and spatial information with a single exposure. Imaging experiments demonstrate that the multispectral images of the target illuminated with white light source can be obtained. Fluorescence images of multiple fluorescence objects (two glass beads filled with 20 uL 1.0 mg/mL quantum dots solutions that emit 530 +/- 15 nm and 620 +/- 15 nm fluorescence, respectively) buried 3 mm below the surface of a tissue mimicking phantom are acquired. The results demonstrate that the system can provide complementary information in fluorescence imaging. The design diagram of the proposed system is given to explain the advantage of compactness and flexibility in integrating with other imaging platforms.

  18. Spectral resolution enhancement of hyperspectral imagery by a multiple-aperture compressive optical imaging system

    Directory of Open Access Journals (Sweden)

    Hoover Fabian Rueda Chacon

    2014-11-01

    Full Text Available The Coded Aperture Snapshot Spectral Imaging (CASSI system captures the three-dimensional (3D spatio-spectral information of a scene using a set of two-dimensional (2D random-coded Focal Plane Array (FPA measurements. A compressive sensing reconstruc-tion algorithm is then used to recover the underlying spatio-spectral 3D data cube. The quality of the reconstructed spectral images depends exclusively on the CASSI sensing matrix, which is determined by the structure of a set of random coded apertures. In this paper, the CASSI system is generalized by developing a multiple-aperture optical imaging system such that spectral resolution en-hancement is attainable. In the proposed system, a pair of high-resolution coded apertures is introduced into the CASSI system, allow-ing it to encode both spatial and spectral characteristics of the hyperspectral image. This approach allows the reconstruction of super-resolved hyperspectral data cubes, where the number of spectral bands is significantly increased and the quality in the spatial domain is greatly improved. Extensively simulated experiments show a gain in the peak-signal-to-noise ratio (PSNR, along with a better fit of the reconstructed spectral signatures to the original spectral data.  

  19. Contrast enhancement of subcutaneous blood vessel images by means of visible and near-infrared hyper-spectral imaging

    Science.gov (United States)

    Katrašnik, Jaka; Bürmen, Miran; Pernuš, Franjo; Likar, Boštjan

    2009-02-01

    Visualization of subcutaneous veins is very difficult with the naked eye, but important for diagnosis of medical conditions and different medical procedures such as catheter insertion and blood withdrawal. Moreover, recent studies showed that the images of subcutaneous veins could be used for biometric identification. The majority of methods used for enhancing the contrast between the subcutaneous veins and surrounding tissue are based on simple imaging systems utilizing CMOS or CCD cameras with LED illumination capable of acquiring images from the near infrared spectral region, usually near 900 nm. However, such simplified imaging methods cannot exploit the full potential of the spectral information. In this paper, a new highly versatile method for enhancing the contrast of subcutaneous veins based on state-of-the-art high-resolution hyper-spectral imaging system utilizing the spectral region from 550 to 1700 nm is presented. First, a detailed analysis of the contrast between the subcutaneous veins and the surrounding tissue as a function of wavelength, for several different positions on the human arm, was performed in order to extract the spectral regions with the highest contrast. The highest contrast images were acquired at 1100 nm, however, combining the individual images from the extracted spectral regions by the proposed contrast enhancement method resulted in a single image with up to ten-fold better contrast. Therefore, the proposed method has proved to be a useful tool for visualization of subcutaneous veins.

  20. A preconditioned inexact newton method for nonlinear sparse electromagnetic imaging

    KAUST Repository

    Desmal, Abdulla

    2015-03-01

    A nonlinear inversion scheme for the electromagnetic microwave imaging of domains with sparse content is proposed. Scattering equations are constructed using a contrast-source (CS) formulation. The proposed method uses an inexact Newton (IN) scheme to tackle the nonlinearity of these equations. At every IN iteration, a system of equations, which involves the Frechet derivative (FD) matrix of the CS operator, is solved for the IN step. A sparsity constraint is enforced on the solution via thresholded Landweber iterations, and the convergence is significantly increased using a preconditioner that levels the FD matrix\\'s singular values associated with contrast and equivalent currents. To increase the accuracy, the weight of the regularization\\'s penalty term is reduced during the IN iterations consistently with the scheme\\'s quadratic convergence. At the end of each IN iteration, an additional thresholding, which removes small \\'ripples\\' that are produced by the IN step, is applied to maintain the solution\\'s sparsity. Numerical results demonstrate the applicability of the proposed method in recovering sparse and discontinuous dielectric profiles with high contrast values.

  1. ANALYSIS OF SPECTRAL CHARACTERISTICS AMONG DIFFERENT SENSORS BY USE OF SIMULATED RS IMAGES

    Institute of Scientific and Technical Information of China (English)

    2000-01-01

    This research, by use of RS image-simulating method, simulated apparent reflectance images at sensor level and ground-reflectance images of SPOT-HRV,CBERS-CCD,Landsat-TM and NOAA14-AVHRR' s corresponding bands. These images were used to analyze sensor's differences caused by spectral sensitivity and atmospheric impacts. The differences were analyzed on Normalized Difference Vegetation Index(NDVI). The results showed that the differences of sensors' spectral characteristics cause changes of their NDVI and reflectance. When multiple sensors' data are applied to digital analysis, the error should be taken into account. Atmospheric effect makes NDVI smaller, and atn~pheric correction has the tendency of increasing NDVI values. The reflectance and their NDVIs of different sensors can be used to analyze the differences among sensor' s features. The spectral analysis method based on RS simulated images can provide a new way to design the spectral characteristics of new sensors.

  2. The spectral combination characteristic of grating and the bi-grating diffraction imaging effect

    Institute of Scientific and Technical Information of China (English)

    2007-01-01

    This paper reports on a new property of grating, namely spectral combination, and on bi-grating diffraction imaging that is based on spectral combination. The spectral combination characteristic of a grating is the capability of combining multiple light beams of different wavelengths incident from specific angles into a single beam. The bi-grating diffraction imaging is the formation of the image of an object with two gratings: the first grating disperses the multi-color light beams from the object and the second combines the dispersed light beams to form the image. We gave the conditions necessary for obtaining the spectral combination. We also presented the equations that relate the two gratings’ spatial frequencies, diffraction orders and positions necessary for obtaining the bi-grating diffraction imaging.

  3. The spectral combination characteristic of grating and the bi-grating diffraction imaging effect

    Institute of Scientific and Technical Information of China (English)

    ZHANG WeiPing; HE XiaoRong

    2007-01-01

    This paper reports on a new property of grating,namely spectral combination,and on bi-grating diffraction imaging that is based on spectral combination.The spectral combination characteristic of a grating is the capability of combining multiple light beams of different wavelengths incident from specific angles into a single beam.The bi-grating diffraction imaging is the formation of the image of an object with two gratings: the first grating disperses the multi-color light beams from the object and the second combines the dispersed light beams to form the image.We gave the conditions necessary for obtaining the spectral combination.We also presented the equations that relate the two gratings' spatial frequencies,diffraction orders and positions necessary for obtaining the bi-grating diffraction imaging.

  4. Comparison of local and global angular interpolation applied to spectral-spatial EPR image reconstruction.

    Science.gov (United States)

    Ahn, Kang-Hyun; Halpern, Howard J

    2007-03-01

    Spectral-spatial images reconstructed from a small number of projections suffer from streak artifacts that are seen as noise, particularly in the spectral dimension. Interpolation in projection space can reduce artifacts in the reconstructed images. The reduction of background artifacts improves lineshape fitting. In this work, we compared the performances of angular interpolation implemented using linear, cubic B-spline, and sinc methods. Line width maps were extracted from 4-D EPR images of phantoms using spectral fitting to evaluate each interpolation method and its robustness to noise. Results from experiment and simulation showed that the cubic B-spline, angular interpolation was preferable to either sinc or linear interpolation methods.

  5. Real-time dispersion-compensated image reconstruction for compressive sensing spectral domain optical coherence tomography.

    Science.gov (United States)

    Xu, Daguang; Huang, Yong; Kang, Jin U

    2014-09-01

    In this work, we propose a novel dispersion compensation method that enables real-time compressive sensing (CS) spectral domain optical coherence tomography (SD OCT) image reconstruction. We show that dispersion compensation can be incorporated into CS SD OCT by multiplying the dispersion-correcting terms by the undersampled spectral data before CS reconstruction. High-quality SD OCT imaging with dispersion compensation was demonstrated at a speed in excess of 70 frames per s using 40% of the spectral measurements required by the well-known Shannon/Nyquist theory. The data processing and image display were performed on a conventional workstation having three graphics processing units.

  6. CARS and non-linear microscopy imaging of brain tumors

    Science.gov (United States)

    Galli, Roberta; Uckermann, Ortrud; Tamosaityte, Sandra; Geiger, Kathrin; Schackert, Gabriele; Steiner, Gerald; Koch, Edmund; Kirsch, Matthias

    2013-06-01

    Nonlinear optical microscopy offers a series of techniques that have the potential to be applied in vivo, for intraoperative identification of tumor border and in situ pathology. By addressing the different content of lipids that characterize the tumors with respect to the normal brain tissue, CARS microscopy enables to discern primary and secondary brain tumors from healthy tissue. A study performed in mouse models shows that the reduction of the CARS signal is a reliable quantity to identify brain tumors, irrespective from the tumor type. Moreover it enables to identify tumor borders and infiltrations at a cellular resolution. Integration of CARS with autogenous TPEF and SHG adds morphological and compositional details about the tissue. Examples of multimodal CARS imaging of different human tumor biopsies demonstrate the ability of the technique to retrieve information useful for histopathological diagnosis.

  7. Noninvasive nonlinear imaging through strongly-scattering turbid layers

    CERN Document Server

    Katz, Ori; Guan, Yefeng; Silberberg, Yaron

    2014-01-01

    Diffraction-limited imaging through complex scattering media is a long sought after goal with important applications in biomedical research. In recent years, high resolution wavefront-shaping has emerged as a powerful approach to generate a sharp focus through highly scattering, visually opaque samples. However, it requires a localized feedback signal from the target point of interest, which necessitates an invasive procedure in all-optical techniques. Here, we show that by exploiting optical nonlinearities, a diffraction-limited focus can be formed inside or through a complex sample, even when the feedback signal is not localized. We prove our approach theoretically and numerically, and experimentally demonstrate it with a two-photon fluorescence signal through highly scattering biological samples. We use the formed focus to perform two-photon microscopy through highly scattering, visually opaque layers.

  8. A sparse electromagnetic imaging scheme using nonlinear landweber iterations

    KAUST Repository

    Desmal, Abdulla

    2015-10-26

    Development and use of electromagnetic inverse scattering techniques for imagining sparse domains have been on the rise following the recent advancements in solving sparse optimization problems. Existing techniques rely on iteratively converting the nonlinear forward scattering operator into a sequence of linear ill-posed operations (for example using the Born iterative method) and applying sparsity constraints to the linear minimization problem of each iteration through the use of L0/L1-norm penalty term (A. Desmal and H. Bagci, IEEE Trans. Antennas Propag, 7, 3878–3884, 2014, and IEEE Trans. Geosci. Remote Sens., 3, 532–536, 2015). It has been shown that these techniques produce more accurate and sharper images than their counterparts which solve a minimization problem constrained with smoothness promoting L2-norm penalty term. But these existing techniques are only applicable to investigation domains involving weak scatterers because the linearization process breaks down for high values of dielectric permittivity.

  9. Envelope based nonlinear blind deconvolution approach for ultrasound imaging

    Directory of Open Access Journals (Sweden)

    L.T. Chira

    2012-06-01

    Full Text Available The resolution of ultrasound medical images is yet an important problem despite of the researchers efforts. In this paper we presents a nonlinear blind deconvolution to eliminate the blurring effect based on the measured radio-frequency signal envelope. This algorithm is executed in two steps. Firslty we make an estimation for Point Spread Function (PSF and, secondly we use the estimated PSF to remove, iteratively their effect. The proposed algorithm is a greedy algorithm, called also matching pursuit or CLEAN. The use of this algorithm is motivated beacause theorically it avoid the so called inverse problem, which usually needs regularization to obtain an optimal solution. The results are presented using 1D simulated signals in term of visual evaluation and nMSE in comparison with the two most kwown regularisation solution methods for least square problem, Thikonov regularization or l2-norm and Total Variation or l1 norm.

  10. Multi-spectral image enhancement algorithm based on keeping original gray level

    Science.gov (United States)

    Wang, Tian; Xu, Linli; Yang, Weiping

    2016-11-01

    Characteristics of multi-spectral imaging system and the image enhancement algorithm are introduced.Because histogram equalization and some other image enhancement will change the original gray level,a new image enhancement algorithm is proposed to maintain the gray level.For this paper, we have chosen 6 narrow-bands multi-spectral images to compare,the experimental results show that the proposed method is better than those histogram equalization and other algorithm to multi-spectral images.It also insures that histogram information contained in original features is preserved and guarantees to make use of data class information.What's more,on the combination of subjective and objective sharpness evaluation,details of the images are enhanced and noise is weaken.

  11. New confocal microscopy hyperspectral imager for NIR-emitting bioprobes: high spectral resolution for a wide spectral range (Conference Presentation)

    Science.gov (United States)

    Marcet, Stéphane; Benayas, Antonio; Quintanilla, Marta; Mangiarini, Francesca; Verhaegen, Marc; Vetrone, Fiorenzo; Blais-Ouellette, Sébastien

    2016-03-01

    Functional nanoscale materials are being extensively investigated for applications in biology and medicine and are ready to make significant contributions in the realization of exciting advancements in diverse areas of diagnostics and therapeutics. Aiming for more accurate, efficient, non-invasive and fast diagnostic tools, the use of near-infrared (NIR) light in the range of the 1st and 2nd biological window (NIR-I: 0.70-0.95 µm; NIR-II: 1.00-1.35 µm) provides deeper penetration depth into biological tissue, better image contrast, reduced phototoxicity and photobleaching. Consequently, NIR-based bioimaging became a quickly emerging field and manifold new NIR-emitting bioprobes have been reported. Since commercially available microscopes are not optimized for this kind of NPs, a new microscopy hyperspectral confocal imager has been developed to cover a broad spectral range (400 to 1700 nm) with high spectral resolution. The smallest spectral variation can be easily monitored thanks to the high spectral resolution (as low as 0.2 nm). This is possible thanks to a combination of an EMCCD and an InGaAs camera with a high resolution spectrometer. An extended number of NPs can be excited with a Ti:Sapphire laser, which provides tunable illumination within 690-1040 nm. Cells and tissues can be mapped in less than 100 ms, allowing in-vivo imaging. As a proof of concept, here we present the preliminary results of the spatial distribution of the fluorescence signal intensity from lanthanide doped nanoparticles incorporated into a system of biological interest. The temperature sub-mm gradient - analyzing the spectral features so gathered through an all-optical route is also thoroughly discussed.

  12. Sources of image degradation in fundamental and harmonic ultrasound imaging using nonlinear, full-wave simulations.

    Science.gov (United States)

    Pinton, Gianmarco F; Trahey, Gregg E; Dahl, Jeremy J

    2011-04-01

    A full-wave equation that describes nonlinear propagation in a heterogeneous attenuating medium is solved numerically with finite differences in the time domain (FDTD). This numerical method is used to simulate propagation of a diagnostic ultrasound pulse through a measured representation of the human abdomen with heterogeneities in speed of sound, attenuation, density, and nonlinearity. Conventional delay-andsum beamforming is used to generate point spread functions (PSF) that display the effects of these heterogeneities. For the particular imaging configuration that is modeled, these PSFs reveal that the primary source of degradation in fundamental imaging is reverberation from near-field structures. Reverberation clutter in the harmonic PSF is 26 dB higher than the fundamental PSF. An artificial medium with uniform velocity but unchanged impedance characteristics indicates that for the fundamental PSF, the primary source of degradation is phase aberration. An ultrasound image is created in silico using the same physical and algorithmic process used in an ultrasound scanner: a series of pulses are transmitted through heterogeneous scattering tissue and the received echoes are used in a delay-and-sum beamforming algorithm to generate images. These beamformed images are compared with images obtained from convolution of the PSF with a scatterer field to demonstrate that a very large portion of the PSF must be used to accurately represent the clutter observed in conventional imaging. © 2011 IEEE

  13. Color image segmentation using watershed and Nyström method based spectral clustering

    Science.gov (United States)

    Bai, Xiaodong; Cao, Zhiguo; Yu, Zhenghong; Zhu, Hu

    2011-11-01

    Color image segmentation draws a lot of attention recently. In order to improve efficiency of spectral clustering in color image segmentation, a novel two-stage color image segmentation method is proposed. In the first stage, we use vector gradient approach to detect color image gradient information, and watershed transformation to get the pre-segmentation result. In the second stage, Nyström extension based spectral clustering is used to get the final result. To verify the proposed algorithm, it is applied to color images from the Berkeley Segmentation Dataset. Experiments show our method can bring promising results and reduce the runtime significantly.

  14. Spectral theory and nonlinear problems Théorie spectrale et problèmes non-linéaires

    Directory of Open Access Journals (Sweden)

    Ahmed Lesfari

    2010-06-01

    Full Text Available We present a Lie algebra theoretical schema leading to integrable systems, based on the Kostant-Kirillov coadjoint action. Many problems on Kostant-Kirillov coadjoint orbits in subalgebras of infinite dimensional Lie algebras (Kac-Moody Lie algebras yield large classes of extended Lax pairs. A general statement leading to such situations is given by the Adler-Kostant-Symes theorem and the van Moerbeke-Mumford linearization method provides an algebraic map from the complex invariant manifolds of these systems to the Jacobi variety (or some subabelian variety of it of the spectral curve. The complex flows generated by the constants of the motion are straight line motions on these varieties. We study the isospectral deformation of periodic Jacobi matrices and general difference operators from an algebraic geometrical point of view and their relation with the Kac-Moody extension of some algebras. We will present in detail the Griffith's aproach and his cohomological interpretation of linearization test for solving integrable systems without reference to Kac-Moody algebras. We will discuss several examples of integrable systems of relevance in mathematical physics.

  15. Large Time-Stepping Spectral Methods for the Semiclassical Limit of the Defocusing Nonlinear Schrödinger Equation

    Directory of Open Access Journals (Sweden)

    Zongqi Liang

    2009-01-01

    Full Text Available We analyze a class of large time-stepping Fourier spectral methods for the semiclassical limit of the defocusing Nonlinear Schrödinger equation and provide highly stable methods which allow much larger time step than for a standard implicit-explicit approach. An extra term, which is consistent with the order of the time discretization, is added to stabilize the numerical schemes. Meanwhile, the first-order and second-order semi-implicit schemes are constructed and analyzed. Finally the numerical experiments are performed to demonstrate the effectiveness of the large time-stepping approaches.

  16. TICMR: Total Image Constrained Material Reconstruction via Nonlocal Total Variation Regularization for Spectral CT.

    Science.gov (United States)

    Liu, Jiulong; Ding, Huanjun; Molloi, Sabee; Zhang, Xiaoqun; Gao, Hao

    2016-12-01

    This work develops a material reconstruction method for spectral CT, namely Total Image Constrained Material Reconstruction (TICMR), to maximize the utility of projection data in terms of both spectral information and high signal-to-noise ratio (SNR). This is motivated by the following fact: when viewed as a spectrally-integrated measurement, the projection data can be used to reconstruct a total image without spectral information, which however has a relatively high SNR; when viewed as a spectrally-resolved measurement, the projection data can be utilized to reconstruct the material composition, which however has a relatively low SNR. The material reconstruction synergizes material decomposition and image reconstruction, i.e., the direct reconstruction of material compositions instead of a two-step procedure that first reconstructs images and then decomposes images. For material reconstruction with high SNR, we propose TICMR with nonlocal total variation (NLTV) regularization. That is, first we reconstruct a total image using spectrally-integrated measurement without spectral binning, and build the NLTV weights from this image that characterize nonlocal image features; then the NLTV weights are incorporated into a NLTV-based iterative material reconstruction scheme using spectrally-binned projection data, so that these weights serve as a high-SNR reference to regularize material reconstruction. Note that the nonlocal property of NLTV is essential for material reconstruction, since material compositions may have significant local intensity variations although their structural information is often similar. In terms of solution algorithm, TICMR is formulated as an iterative reconstruction method with the NLTV regularization, in which the nonlocal divergence is utilized based on the adjoint relationship. The alternating direction method of multipliers is developed to solve this sparsity optimization problem. The proposed TICMR method was validated using both simulated

  17. Multi-spectral image fusion method based on two channels non-separable wavelets

    Institute of Scientific and Technical Information of China (English)

    LIU Bin; PENG JiaXiong

    2008-01-01

    A construction method of two channels non-separable wavelets filter bank which dilation matrix is [1, 1; 1, -1] and its application in the fusion of multi-spectral image are presented. Many 4x4 filter banks are designed. The multi-spectral image fusion algorithm based on this kind of wavelet is proposed. Using this filter bank, multi-resolution wavelet decomposition of the intensity of multi-spectral image and panchromatic image is performed, and the two low-frequency components of the intensity and the panchromatic image are merged by using a tradeoff parameter. The experiment results show that this method is good in the preservation of spectral quality and high spatial resolution information. Its performance in preserving spectral quality and high spatial information is better than the fusion method based on DWFT and IHS. When the parameter t is closed to 1, the fused image can obtain rich spectral information from the original MS image. The amount of computation reduced to only half of the fusion method based on four channels wavelet transform.

  18. HIGH-ACCURACY BAND TO BAND REGISTRATION METHOD FOR MULTI-SPECTRAL IMAGES OF HJ-1A/B

    Institute of Scientific and Technical Information of China (English)

    Lu Hao; Liu Tuanjie; Zhao Haiqing

    2012-01-01

    Band-to-band registration accuracy is an important parameter of multispectral data.A novel band-to-band registration approach with high precision is proposed for the multi-spectral images of HJ-1A/B.Firstly,the main causes resulted in misregistration are analyzed,and a high-order polynomial model is proposed.Secondly,a phase fringe filtering technique is employed to Phase Correlation Method based on Singular Value Decomposition (SVD-PCM) for reducing the noise in phase difference matrix.Then,experiments are carried out to build nonlinear registration models,and images of green band and red band are aligned to blue band with an accuracy of 0.1 pixels,while near infrared band with an accuracy of 0.2 pixels.

  19. Nonlinear imaging (NIM) of flaws in a complex composite stiffened panel using a constructive nonlinear array (CNA) technique.

    Science.gov (United States)

    Malfense Fierro, Gian Piero; Meo, Michele

    2017-02-01

    Recently, there has been high interest in the capabilities of nonlinear ultrasound techniques for damage/defect detection as these techniques have been shown to be quite accurate in imaging some particular type of damage. This paper presents a Constructive Nonlinear Array (CNA) method, for the detection and imaging of material defects/damage in a complex composite stiffened panel. CNA requires the construction of an ultrasound array in a similar manner to standard phased arrays systems, which require multiple transmitting and receiving elements. The method constructively phase-match multiple captured signals at a particular position given multiple transmit positions, similar to the total focusing method (TFM) method. Unlike most of the ultrasonic linear techniques, a longer excitation signal was used to achieve a steady-state excitation at each capturing position, so that compressive and tensile stress at defect/crack locations increases the likelihood of the generation of nonlinear elastic waves. Moreover, the technique allows the reduction of instrumentation nonlinear wave generation by relying on signal attenuation to naturally filter these errors. Experimental tests were carried out on a stiffened panel with manufacturing defects. Standard industrial linear ultrasonic test were carried out for comparison. The proposed new method allows to image damages/defects in a reliable and reproducible manner and overcomes some of the main limitations of nonlinear ultrasound techniques. In particular, the effectiveness and robustness of CNA and the advantages over linear ultrasonic were clearly demonstrated allowing a better resolution and imaging of complex and realistic flaws.

  20. Nonlinear color-image decomposition for image processing of a digital color camera

    Science.gov (United States)

    Saito, Takahiro; Aizawa, Haruya; Yamada, Daisuke; Komatsu, Takashi

    2009-01-01

    This paper extends the BV (Bounded Variation) - G and/or the BV-L1 variational nonlinear image-decomposition approaches, which are considered to be useful for image processing of a digital color camera, to genuine color-image decomposition approaches. For utilizing inter-channel color cross-correlations, this paper first introduces TV (Total Variation) norms of color differences and TV norms of color sums into the BV-G and/or BV-L1 energy functionals, and then derives denoising-type decomposition-algorithms with an over-complete wavelet transform, through applying the Besov-norm approximation to the variational problems. Our methods decompose a noisy color image without producing undesirable low-frequency colored artifacts in its separated BV-component, and they achieve desirable high-quality color-image decomposition, which is very robust against colored random noise.

  1. Band selection for nonlinear unmixing of hyperspectral images as a maximal clique problem.

    Science.gov (United States)

    Imbiriba, Tales; Bermudez, Jose Carlos; Richard, Cedric

    2017-03-01

    Kernel-based nonlinear mixing models have been applied to unmix spectral information of hyperspectral images when the type of mixing occurring in the scene is too complex or unknown. Such methods, however, usually require the inversion of matrices of sizes equal to the number of spectral bands. Reducing the computational load of these methods remains a challenge in large scale applications. This paper proposes a centralized band selection (BS) method for supervised unmixing in the reproducing kernel Hilbert space (RKHS). It is based upon the coherence criterion, which sets the largest value allowed for correlations between the basis kernel functions characterizing the selected bands in the unmixing model. We show that the proposed BS approach is equivalent to solving a maximum clique problem (MCP), i.e., searching for the biggest complete subgraph in a graph. Furthermore, we devise a strategy for selecting the coherence threshold and the Gaussian kernel bandwidth using coherence bounds for linearly independent bases. Simulation results illustrate the efficiency of the proposed method.

  2. Increased spectral bandwidths in nonlinear conversion processes by use of multicrystal designs.

    Science.gov (United States)

    Brown, M

    1998-10-15

    The fourth-harmonic generation of broadband 243-nm radiation is reported. The broadband radiation is achieved by implementation of a multicrystal design to overcome spectral bandwidth limitations, and a plane-wave analysis is developed that shows increased spectral bandwidths for these designs. The fourth harmonic of a Cr:LiSAF laser operating at 972 nm is generated in beta-barium borate (BBO). The results demonstrate a spectral bandwidth at 243 nm more than five times broader than that which is expected from a single BBO crystal of equivalent length.

  3. Evaluation of spectral coherence estimation methods for endmembers selection in hyperspectral images

    Directory of Open Access Journals (Sweden)

    David Fernandes

    2005-08-01

    Full Text Available The right endmenbers choice is an important task in the hiperspectral image classification processes. Among several models that use the endmenbers there is the Linear Spectral Mixture (LSM. This model has been extensively used in the fractional abundance images estimation. This work proposes two semi supervised methods for endmenbers selection based in the spectral coherence selection, which is an extension of the correlation coefficient concept. Spectral samples associated to classes are choosed a priori. These candidate samples to endmembers are compared by its relative spectral coherence. A subset of samples with minimum relative coherence will be selected as final endmenbers. AVIRIS (Airborne Visible/InfraRed Imaging Spectrometer images are used to test and compare the proposed methods.

  4. Bandwidth Controllable Tunable Filter for Hyper-/Multi-Spectral Imager Project

    Data.gov (United States)

    National Aeronautics and Space Administration — This SBIR Phase I proposal introduces a fast speed bandwidth controllable tunable filter for hyper-/multi-spectral (HS/MS) imagers. It dynamically passes a variable...

  5. High Spectral Resolution, High Cadence, Imaging X-ray Microcalorimeters for Solar Physics - Phase 2 Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Microcalorimeter x-ray instruments are non-dispersive, high spectral resolution, broad-band, high cadence imaging spectrometers. We have been developing these...

  6. Conjugate Etalon Spectral Imager (CESI) & Scanning Etalon Methane Mapper (SEMM) Project

    Data.gov (United States)

    National Aeronautics and Space Administration — Development of the CESI focal plane and optics technology will lead to miniaturized hyperspectral and SWIR-band spectral imaging instrumentation compatible with...

  7. A Spectral Signature Shape-Based Algorithm for Landsat Image Classification

    Directory of Open Access Journals (Sweden)

    Yuanyuan Chen

    2016-08-01

    Full Text Available Land-cover datasets are crucial for earth system modeling and human-nature interaction research at local, regional and global scales. They can be obtained from remotely sensed data using image classification methods. However, in processes of image classification, spectral values have received considerable attention for most classification methods, while the spectral curve shape has seldom been used because it is difficult to be quantified. This study presents a classification method based on the observation that the spectral curve is composed of segments and certain extreme values. The presented classification method quantifies the spectral curve shape and takes full use of the spectral shape differences among land covers to classify remotely sensed images. Using this method, classification maps from TM (Thematic mapper data were obtained with an overall accuracy of 0.834 and 0.854 for two respective test areas. The approach presented in this paper, which differs from previous image classification methods that were mostly concerned with spectral “value” similarity characteristics, emphasizes the "shape" similarity characteristics of the spectral curve. Moreover, this study will be helpful for classification research on hyperspectral and multi-temporal images.

  8. Multispectral endoscopy and microscopy imaging system using a spectrally programmable light engine

    Science.gov (United States)

    MacKinnon, N.; Stange, Ulrich; Lane, Pierre M.; MacAulay, Calum E.

    2005-03-01

    We report a spectrally and temporally programmable light engine based on a spatial light modulator that can dynamically create any narrow or broadband spectral profile for hyperspectral, fluorescence, or principal component imaging. Most hyperspectral or multispectral imaging systems use wavelength selection devices such as acousto-optic tunable filters (AOTFs), tunable grating or prism-based monochromators, or filter wheels. While these devices can select wavelengths they cannot create arbitrary spectral profiles. This simple and economical system can be controlled at high speed (up to 5000 illumination profiles per second). Digitally controlled illumination is bit additive with image data providing high dynamic range imaging with monochrome or color imaging devices. This is especially advantageous for endoscopes employing small well CCD or CMOS sensors since the dynamic range now can extend beyond the limits of the sensor itself. In this report we show multispectral images of in vivo tissue and in vitro tissue samples using endoscopes, surgical microscopes and conventional microscopes.

  9. Multimodal nonlinear optical imaging of cartilage development in mouse model

    Science.gov (United States)

    He, Sicong; Xue, Wenqian; Sun, Qiqi; Li, Xuesong; Huang, Jiandong; Qu, Jianan Y.

    2017-02-01

    Kinesin-1 is a kind of motor protein responsible for intracellular transportation and has been studied in a variety of tissues. However, its roles in cartilage development are not clear. In this study, a kinesin-1 heavy chain (Kif5b) knockout mouse model is used to study the functions of kinesin-1 in the cartilage development. We developed a multimodal nonlinear optical (NLO) microscope system integrating stimulated Raman scattering (SRS), second harmonic generation (SHG) and two-photon excited fluorescence (TPEF) to investigate the morphological and biomedical characteristics of fresh tibial cartilage from normal and mutant mice at different developmental stages. The combined forward and backward SHG imaging resolved the fine structure of collagen fibrils in the extracellular matrix of cartilage. Meanwhile, the chondrocyte morphology in different zones of cartilage was visualized by label-free SRS and TPEF images. The results show that the fibrillar collagen in the superficial zone of cartilage in postnatal day 10 and 15 (P10 and P15) knockout mice was significantly less than that of control mice. Moreover, we observed distorted morphology and disorganization of columnar arrangement of chondrocytes in the growth plate cartilage of mutant mice. This study reveals the significant roles of kinesin-1 in collagen formation and chondrocyte morphogenesis.

  10. Segmentation of cDNA Microarray Images using Parallel Spectral Clustering

    Directory of Open Access Journals (Sweden)

    Sandrine MOUYSSET

    2013-05-01

    Full Text Available Microarray technology generates large amounts of expression level of genes to be analyzed simultaneously. This analysis implies microarray image segmentation to extract the quantitative information from spots. Spectral clustering is one of the most relevant unsupervised methods able to gather data without a priori information on shapes or locality. We propose and test on microarray images a parallel strategy for the Spectral Clustering method based on domain decomposition with a criterion to determine the number of clusters.

  11. Segmentation of cDNA Microarray Images using Parallel Spectral Clustering

    Directory of Open Access Journals (Sweden)

    Daniel RUIZ

    2013-05-01

    Full Text Available Microarray technology generates large amounts of expression level of genes to be analyzed simultaneously. This analysis implies microarray image segmentation to extract the quantitative information from spots. Spectral clustering is one of the most relevant unsupervised methods able to gather data without a priori information on shapes or locality. We propose and test on microarray images a parallel strategy for the Spectral Clustering method based on domain decomposition with a criterion to determine the number of clusters.

  12. Optical imaging of hemoglobin oxygen saturation using a small number of spectral images for endoscopic application

    Science.gov (United States)

    Saito, Takaaki; Yamaguchi, Hiroshi

    2015-12-01

    Tissue hypoxia is associated with tumor and inflammatory diseases, and detection of hypoxia is potentially useful for their detailed diagnosis. An endoscope system that can optically observe hemoglobin oxygen saturation (StO2) would enable minimally invasive, real-time detection of lesion hypoxia in vivo. Currently, point measurement of tissue StO2 via endoscopy is possible using the commercial fiber-optic oximeter T-Stat, which is based on visible light spectroscopy at many wavelengths. For clinical use, however, imaging of StO2 is desirable to assess the distribution of tissue oxygenation around a lesion. Here, we describe our StO2 imaging technique based on a small number of wavelength ranges in the visible range. By assuming a homogeneous tissue, we demonstrated that tissue StO2 can be obtained independently from the scattering property and blood concentration of tissue using four spectral bands. We developed a prototype endoscope system and used it to observe tissue-simulating phantoms. The StO2 (%) values obtained using our technique agreed with those from the T-Stat within 10%. We also showed that tissue StO2 can be derived using three spectral band if the scattering property is fixed at preliminarily measured values.

  13. Medical Image Fusion Algorithm Based on Nonlinear Approximation of Contourlet Transform and Regional Features

    Directory of Open Access Journals (Sweden)

    Hui Huang

    2017-01-01

    Full Text Available According to the pros and cons of contourlet transform and multimodality medical imaging, here we propose a novel image fusion algorithm that combines nonlinear approximation of contourlet transform with image regional features. The most important coefficient bands of the contourlet sparse matrix are retained by nonlinear approximation. Low-frequency and high-frequency regional features are also elaborated to fuse medical images. The results strongly suggested that the proposed algorithm could improve the visual effects of medical image fusion and image quality, image denoising, and enhancement.

  14. Spectral Imaging of Multi-Color Chromogenic Dyes in Pathological Specimens

    Directory of Open Access Journals (Sweden)

    Merryn V. E. Macville

    2001-01-01

    Full Text Available We have investigated the use of spectral imaging for multi‐color analysis of permanent cytochemical dyes and enzyme precipitates on cytopathological specimens. Spectral imaging is based on Fourier‐transform spectroscopy and digital imaging. A pixel‐by‐pixel spectrum‐based color classification is presented of single‐, double‐, and triple‐color in situ hybridization for centromeric probes in T24 bladder cancer cells, and immunocytochemical staining of nuclear antigens Ki‐67 and TP53 in paraffin‐embedded cervical brush material (AgarCyto. The results demonstrate that spectral imaging unambiguously identifies three chromogenic dyes in a single bright‐field microscopic specimen. Serial microscopic fields from the same specimen can be analyzed using a spectral reference library. We conclude that spectral imaging of multi‐color chromogenic dyes is a reliable and robust method for pixel color recognition and classification. Our data further indicate that the use of spectral imaging (a may increase the number of parameters studied simultaneously in pathological diagnosis, (b may provide quantitative data (such as positive labeling indices more accurately, and (c may solve segmentation problems currently faced in automated screening of cell‐ and tissue specimens. Figures on http://www.esacp.org/acp/2001/22‐3/macville.htm.

  15. Growth, spectral, optical, thermal, crystallization perfection and nonlinear optical studies of novel nonlinear optical crystal—Urea thiosemicarbazone monohydrate

    Science.gov (United States)

    Hanumantharao, Redrothu; Kalainathan, S.; Bhagavannarayana, G.

    2012-06-01

    Single crystals of organic nonlinear material urea thiosemicarbazone monohydrate (UTM) have been grown by slow evaporation method. The grown crystals were characterized by single crystal X-ray diffraction analysis reveals that sample crystallized in triclinic system with noncentrosymmetric space group P1. Powder XRD pattern confirmed that grown crystal posses highly crystalline nature. FTIR spectrum was recorded to identify the presence of functional groups and molecular structure was confirmed by 1H NMR spectrum. Material confirmation of title compound has been performed by using mass spectroscopic analysis. Elemental composition of grown crystal was confirmed by energy-dispersive spectrometry (EDS). To study the crystalline perfection of the grown crystals, high-resolution X-ray diffraction (HR-XRD) study was carried out. Thermogravimetric and differential thermal analyses were employed to understand the thermal and physio-chemical stability of the synthesized compound. UV-Vis-NIR spectrum revealed the transmission properties of the crystal specimen. Relative SHG efficiency is measured by Kurtz and Perry method and found to about 0.89 times that of standard potassium dihydrogen phosphate (KDP) crystals.

  16. Passive Standoff Super Resolution Imaging using Spatial-Spectral Multiplexing

    Science.gov (United States)

    2017-08-14

    with a Fourier transform spectrometer, requiring the FTAS system to operate in the near - infrared , which need only effect the coatings and FPE...A. Cook, and J. Hair, “ System analysis of a tilted field-widened Michelson interferometer for high spectral resolution lidar ”, Opt. Expr. Vol. 20, No...General Fabry-Perot System ................................................ 48 2.6 Tolerancing and Aberrations

  17. Spectral compression algorithms for the analysis of very large multivariate images

    Science.gov (United States)

    Keenan, Michael R.

    2007-10-16

    A method for spectrally compressing data sets enables the efficient analysis of very large multivariate images. The spectral compression algorithm uses a factored representation of the data that can be obtained from Principal Components Analysis or other factorization technique. Furthermore, a block algorithm can be used for performing common operations more efficiently. An image analysis can be performed on the factored representation of the data, using only the most significant factors. The spectral compression algorithm can be combined with a spatial compression algorithm to provide further computational efficiencies.

  18. Visible spectral imager for occultation and nightglow (VISION) for the PICASSO Mission

    Science.gov (United States)

    Saari, Heikki; Näsilä, Antti; Holmlund, Christer; Mannila, Rami; Näkki, Ismo; Ojanen, Harri J.; Fussen, Didier; Pieroux, Didier; Demoulin, Philippe; Dekemper, Emmanuel; Vanhellemont, Filip

    2015-10-01

    PICASSO - A PICo-satellite for Atmospheric and Space Science Observations is an ESA project led by the Belgian Institute for Space Aeronomy, in collaboration with VTT, Clyde Space Ltd. (UK), and the Centre Spatial de Liège (BE). VTT Technical Research Centre of Finland Ltd. will deliver the Visible Spectral Imager for Occultation and Nightglow (VISION) for the PICASSO mission. The VISION targets primarily the observation of the Earth's atmospheric limb during orbital Sun occultation. By assessing the radiation absorption in the Chappuis band for different tangent altitudes, the vertical profile of the ozone is retrieved. A secondary objective is to measure the deformation of the solar disk so that stratospheric and mesospheric temperature profiles are retrieved by inversion of the refractive raytracing problem. Finally, occasional full spectral observations of polar auroras are also foreseen. The VISION design realized with commercial of the shelf (CoTS) parts is described. The VISION instrument is small, lightweight (~500 g), Piezo-actuated Fabry-Perot Interferometer (PFPI) tunable spectral imager operating in the visible and near-infrared (430 - 800 nm). The spectral resolution over the whole wavelength range will be better than 10 nm @ FWHM. VISION has is 2.5° x 2.5° total field of view and it delivers maximum 2048 x 2048 pixel spectral images. The sun image size is around 0.5° i.e. ~500 pixels. To enable fast spectral data image acquisition VISION can be operated with programmable image sizes. VTT has previously developed PFPI tunable filter based AaSI Spectral Imager for the Aalto-1 Finnish CubeSat. In VISION the requirements of the spectral resolution and stability are tighter than in AaSI. Therefore the optimization of the of the PFPI gap control loop for the operating temperature range and vacuum conditions has to be improved. VISION optical, mechanical and electrical design is described.

  19. Hyper-Spectral Imager in visible and near-infrared band for lunar compositional mapping

    Indian Academy of Sciences (India)

    A S Kiran Kumar; A Roy Chowdhury

    2005-12-01

    India ’s first lunar mission,Chandrayaan-1,will have a Hyper-Spectral Imager in the visible and near-infrared spectral bands along with other instruments.The instrument will enable mineralogical mapping of the Moon ’s crust in a large number of spectral channels.The planned Hyper-Spectral Imager will be the first instrument to map the lunar surface with the capability of resolving the spectral region,0.4 to 0.92 m in 64 continuous bands with a resolution of better than 15 nm and a spatial resolution of 80 m.Spectral separation will be done using a wedge filter and the image will be mapped onto an area detector.The detector output will be processed in the front-end processor to generate the 64-band data with 12-bit quantization.This paper gives a description of the Hyper-Spectral Imager instrument.

  20. Smoothing of Fused Spectral Consistent Satellite Images with TV-based Edge Detection

    DEFF Research Database (Denmark)

    Sveinsson, Johannes; Aanæs, Henrik; Benediktsson, Jon Atli

    2007-01-01

    Several widely used methods have been proposed for fusing high resolution panchromatic data and lower resolution multi-channel data. However, many of these methods fail to maintain the spectral consistency of the fused high resolution image, which is of high importance to many of the applications...... based on satellite data. Additionally, most conventional methods are loosely connected to the image forming physics of the satellite image, giving these methods an ad hoc feel. Vesteinsson et al. [1] proposed a method of fusion of satellite images that is based on the properties of imaging physics...... in a statistically meaningful way and was called spectral consistent panshapening (SCP). In this paper we improve this framework for satellite image fusion by introducing a better image prior, via data-dependent image smoothing. The dependency is obtained via total variation edge detection method....

  1. Hyperspectral Image Land Cover Classification Algorithm Based on Spatial-spectral Coordination Embedding

    Directory of Open Access Journals (Sweden)

    HUANG Hong

    2016-08-01

    Full Text Available Aiming at the problem that in hyperspectral image land cover classification, the traditional classification methods just apply the spectral information while they ignore the relationship between the spatial neighbors, a new dimensionality algorithm called spatial-spectral coordination embedding (SSCE and a new classifier called spatial-spectral coordination nearest neighbor (SSCNN were proposed in this paper. Firstly, the proposed method defines a spatial-spectral coordination distance and the distance is applied to the neighbor selection and low-dimensional embedding. Then, it constructs a spatial-spectral neighborhood graph to maintain the manifold structure of the data set, and enhances the aggregation of data through raising weight of the spatial neighbor points to extract the discriminant features. Finally, it uses the SSCNN to classify the reduced dimensional data. Experimental results using PaviaU and Salinas data set show that the proposed method can effectively improve ground objects classification accuracy comparing with traditional spectral classification methods.

  2. Robust Fusion of Multi-Band Images with Different Spatial and Spectral Resolutions for Change Detection

    CERN Document Server

    Ferraris, Vinicius; Wei, Qi; Chabert, Marie

    2016-01-01

    Archetypal scenarios for change detection generally consider two images acquired through sensors of the same modality. However, in some specific cases such as emergency situations, the only images available may be those acquired through different kinds of sensors. More precisely, this paper addresses the problem of detecting changes between two multi-band optical images characterized by different spatial and spectral resolutions. This sensor dissimilarity introduces additional issues in the context of operational change detection. To alleviate these issues, classical change detection methods are applied after independent preprocessing steps (e.g., resampling) used to get the same spatial and spectral resolutions for the pair of observed images. Nevertheless, these preprocessing steps tend to throw away relevant information. Conversely, in this paper, we propose a method that more effectively uses the available information by modeling the two observed images as spatial and spectral versions of two (unobserved)...

  3. Hard X-Ray Imaging of Individual Spectral Components in Solar Flares

    CERN Document Server

    Caspi, Amir; McTiernan, James M; Krucker, Säm

    2015-01-01

    We present a new analytical technique, combining Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI) high-resolution imaging and spectroscopic observations, to visualize solar flare emission as a function of spectral component (e.g., isothermal temperature) rather than energy. This computationally inexpensive technique is applicable to all spatially-invariant spectral forms and is useful for visualizing spectroscopically-determined individual sources and placing them in context, e.g., comparing multiple isothermal sources with nonthermal emission locations. For example, while extreme ultraviolet images can usually be closely identified with narrow temperature ranges, due to the emission being primarily from spectral lines of specific ion species, X-ray images are dominated by continuum emission and therefore have a broad temperature response, making it difficult to identify sources of specific temperatures regardless of the energy band of the image. We combine RHESSI calibrated X-ray visibilities wi...

  4. Investigation into image quality difference between total variation and nonlinear sparsifying transform based compressed sensing

    Science.gov (United States)

    Dong, Jian; Kudo, Hiroyuki

    2017-03-01

    Compressed sensing (CS) is attracting growing concerns in sparse-view computed tomography (CT) image reconstruction. The most standard approach of CS is total variation (TV) minimization. However, images reconstructed by TV usually suffer from distortions, especially in reconstruction of practical CT images, in forms of patchy artifacts, improper serrate edges and loss of image textures. Most existing CS approaches including TV achieve image quality improvement by applying linear transforms to object image, but linear transforms usually fail to take discontinuities into account, such as edges and image textures, which is considered to be the key reason for image distortions. Actually, discussions on nonlinear filter based image processing has a long history, leading us to clarify that the nonlinear filters yield better results compared to linear filters in image processing task such as denoising. Median root prior was first utilized by Alenius as nonlinear transform in CT image reconstruction, with significant gains obtained. Subsequently, Zhang developed the application of nonlocal means-based CS. A fact is gradually becoming clear that the nonlinear transform based CS has superiority in improving image quality compared with the linear transform based CS. However, it has not been clearly concluded in any previous paper within the scope of our knowledge. In this work, we investigated the image quality differences between the conventional TV minimization and nonlinear sparsifying transform based CS, as well as image quality differences among different nonlinear sparisying transform based CSs in sparse-view CT image reconstruction. Additionally, we accelerated the implementation of nonlinear sparsifying transform based CS algorithm.

  5. Pigment Identification of Paintings Based on Kubelka-Munk Theory and Spectral Images

    Science.gov (United States)

    Moghareh Abed, Farhad

    The preservation of cultural heritage and treatment thereof are delicate responsibilities that demand the best possible technologies and extreme care to avoid any irreversible loss. It necessitates a deep understanding of constituent materials, along with the analytical methods and cutting-edge technologies. Considering this direction, the goal of this dissertation is to promote the conservation procedures by providing an applicable workflow for spectral-based pigment identification. The proposed pipeline is a novel and practical aid for museum conservators for many aspects, such as inpainting, treatment and archiving of artwork. Spectral-based pigment identification algorithms rely on accurate spectral data, a subtractive mixing model and an effective unmixing algorithm. In this dissertation, the spectral data were obtained using a spectral image acquisition system as a feasible and non-destructive technique. A liquid-crystal tunable filter (LCTF) and a CCD camera were used for spectral measurement of the painting. The spectral accuracy and precision of the LCTF-based spectral acquisition system were assessed and enhanced. Of the common factors affecting the acquisition performance, capturing geometry, LCTF angular dependencies and spectral characterization algorithm were new contributions to the traditional workflow. The complexity of subtractive mixtures limits the effective application of linear unmixing algorithms for pigment identification. Accordingly, a new linear modification of single-constant Kubelka-Munk theory was derived to enable the use of available linear spectral unmixing algorithms for paint mixtures. A selection of geometric and iterative-based unmixing algorithms was applied to the LCTF spectral images in the subtractive mixing space using the defined subtractive linear model. Final sets of primary pigments were improved employing a pre-existing database of common pigments as a tool for practical inpainting procedures. The pigment maps, showing

  6. Temporal, Spectral, and Polarization Dependence of the Nonlinear Optical Response of Carbon Disulfide

    Science.gov (United States)

    2014-12-18

    300.6420) Spectroscopy, nonlinear; (190.3270) Kerr effect; (320.7110) Ultrafast nonlinear optics. http://dx.doi.org/10.1364/ OPTICA .1.000436 1...10$15/0$15.00 © 2014 Optical Society of America Research Article Vol. 1, No. 6 / December 2014 / Optica 436 Report Documentation Page Form ApprovedOMB...described by rd t Cd 1 − e− t τr;d e − tτf ;dΘt ; (5) Research Article Vol. 1, No. 6 / December 2014 / Optica 437 where the subscript d

  7. Nonlinear evolution equations associated with the chiral-field spectral problem

    Energy Technology Data Exchange (ETDEWEB)

    Bruschi, M.; Ragnisco, O. (Istituto Nazionale di Fisica Nucleare, Roma (Italy); Dipt. di Fisica, Univ. Rome (Italy))

    1985-08-11

    In this paper we derive and investigate the class of nonlinear evolution equations (NEEs) associated with the linear problem psisub(x) = lambdaApsi. It turns out that many physically interesting NEEs pertain to this class: for instance, the chiral-field equation, the nonlinear Klein-Gordon equations, the Heisenberg and Papanicolau spin chain models, the modified Boussinesq equation, the Wadati-Konno-Ichikawa equations, etc. We display also the Baecklund transformations for such a class and exploit them to derive in a special case the one-soliton solution.

  8. Multi-temporal and multi-source remote sensing image classification by nonlinear relative normalization

    Science.gov (United States)

    Tuia, Devis; Marcos, Diego; Camps-Valls, Gustau

    2016-10-01

    Remote sensing image classification exploiting multiple sensors is a very challenging problem: data from different modalities are affected by spectral distortions and mis-alignments of all kinds, and this hampers re-using models built for one image to be used successfully in other scenes. In order to adapt and transfer models across image acquisitions, one must be able to cope with datasets that are not co-registered, acquired under different illumination and atmospheric conditions, by different sensors, and with scarce ground references. Traditionally, methods based on histogram matching have been used. However, they fail when densities have very different shapes or when there is no corresponding band to be matched between the images. An alternative builds upon manifold alignment. Manifold alignment performs a multidimensional relative normalization of the data prior to product generation that can cope with data of different dimensionality (e.g. different number of bands) and possibly unpaired examples. Aligning data distributions is an appealing strategy, since it allows to provide data spaces that are more similar to each other, regardless of the subsequent use of the transformed data. In this paper, we study a methodology that aligns data from different domains in a nonlinear way through kernelization. We introduce the Kernel Manifold Alignment (KEMA) method, which provides a flexible and discriminative projection map, exploits only a few labeled samples (or semantic ties) in each domain, and reduces to solving a generalized eigenvalue problem. We successfully test KEMA in multi-temporal and multi-source very high resolution classification tasks, as well as on the task of making a model invariant to shadowing for hyperspectral imaging.

  9. Analysis of nonlinear frequency mixing in 1D waveguides with a breathing crack using the spectral finite element method

    Science.gov (United States)

    Joglekar, D. M.; Mitra, M.

    2015-11-01

    A breathing crack, due to its bilinear stiffness characteristics, modifies the frequency spectrum of a propagating dual-frequency elastic wave, and gives rise to sidebands around the probing frequency. This paper presents an analytical-numerical method to investigate such nonlinear frequency mixing resulting from the modulation effects induced by a breathing crack in 1D waveguides, such as axial rods and the Euler-Bernoulli beams. A transverse edge-crack is assumed to be present in both the waveguides, and the local flexibility caused by the crack is modeled using an equivalent spring approach. A simultaneous treatment of both the waveguides, in the framework of the Fourier transform based spectral finite element method, is presented for analyzing their response to a dual frequency excitation applied in the form of a tone-burst signal. The intermittent contact between the crack surfaces is accounted for by introducing bilinear contact forces acting at the nodes of the damage spectral element. Subsequently, an iterative approach is outlined for solving the resulting system of nonlinear simultaneous equations. Applicability of the proposed method is demonstrated by considering several test cases. The existence of sidebands and the higher order harmonics is confirmed in the frequency domain response of both the waveguides under investigation. A qualitative comparison with the previous experimental observations accentuates the utility of the proposed solution method. Additionally, the influence of the two constituent frequencies in the dual frequency excitation is assessed by varying the relative strengths of their amplitudes. A brief parametric study is performed for bringing out the effects of the relative crack depth and crack location on the degree of modulation, which is quantified in terms of the modulation parameter. Results of the present investigation can find their potential use in providing an analytical-numerical support to the studies geared towards the

  10. Biomedical Applications of the Information-efficient Spectral Imaging Sensor (ISIS)

    Energy Technology Data Exchange (ETDEWEB)

    Gentry, S.M.; Levenson, R.

    1999-01-21

    The Information-efficient Spectral Imaging Sensor (ISIS) approach to spectral imaging seeks to bridge the gap between tuned multispectral and fixed hyperspectral imaging sensors. By allowing the definition of completely general spectral filter functions, truly optimal measurements can be made for a given task. These optimal measurements significantly improve signal-to-noise ratio (SNR) and speed, minimize data volume and data rate, while preserving classification accuracy. The following paper investigates the application of the ISIS sensing approach in two sample biomedical applications: prostate and colon cancer screening. It is shown that in these applications, two to three optimal measurements are sufficient to capture the majority of classification information for critical sample constituents. In the prostate cancer example, the optimal measurements allow 8% relative improvement in classification accuracy of critical cell constituents over a red, green, blue (RGB) sensor. In the colon cancer example, use of optimal measurements boost the classification accuracy of critical cell constituents by 28% relative to the RGB sensor. In both cases, optimal measurements match the performance achieved by the entire hyperspectral data set. The paper concludes that an ISIS style spectral imager can acquire these optimal spectral images directly, allowing improved classification accuracy over an RGB sensor. Compared to a hyperspectral sensor, the ISIS approach can achieve similar classification accuracy using a significantly lower number of spectral samples, thus minimizing overall sample classification time and cost.

  11. Automatic endmember selection and nonlinear spectral unmixing of Lunar analog minerals

    Science.gov (United States)

    Rommel, Daniela; Grumpe, Arne; Felder, Marian Patrik; Wöhler, Christian; Mall, Urs; Kronz, Andreas

    2017-03-01

    While the interpretation of spectral reflectance data has been widely applied to detect the presence of minerals, determining and quantifying the abundances of minerals contained by planetary surfaces is still an open problem. With this paper we address one of the two main questions arising from the spectral unmixing problem. While the mathematical mixture model has been extensively researched, considerably less work has been committed to the selection of endmembers from a possibly huge database or catalog of potential endmembers. To solve the endmember selection problem we define a new spectral similarity measure that is not purely based on the reconstruction error, i.e. the squared difference between the modeled and the measured reflectance spectrum. To select reasonable endmembers, we extend the similarity measure by adding information extracted from the spectral absorption bands. This will allow for a better separation of spectrally similar minerals. Evaluating all possible subsets of a possibly very large catalog that contain at least one endmember leads to an exponential increase in computational complexity, rendering catalogs of 20-30 endmembers impractical. To overcome this computational limitation, we propose the usage of a genetic algorithm that, while initially starting with random subsets, forms new subsets by combining the best subsets and, to some extent, does a local search around the best subsets by randomly adding a few endmembers. A Monte-Carlo simulation based on synthetic mixtures and a catalog size varying from three to eight endmembers demonstrates that the genetic algorithm is expected to require less combinations to be evaluated than an exhaustive search if the catalog comprises 10 or more endmembers. Since the genetic algorithm evaluates some combinations multiple times, we propose a simple modification and store previously evaluated endmember combinations. The resulting algorithm is shown to never require more function evaluations than a

  12. J-Inner-Outer Factorization, J-Spectral Factorization, and Robust Control for Nonlinear Systems

    NARCIS (Netherlands)

    Ball, Joseph A.; Schaft, Arjan J. van der

    1996-01-01

    The problem of expressing a given nonlinear state-space system as the cascade connection of a lossless system and a stable, minimum-phase system (inner-outer factorization) is solved for the case of a stable system having state-space equations affine in the inputs. The solution is given in terms of

  13. Enhanced Spectral Modeling of Sparse Aperture Imaging Systems

    Science.gov (United States)

    2007-11-02

    Optical Society of America 61, 272-273. [19] Gonzalez , Rafael C. and R.E. Woods (2002). Digital Image Processing . Second Ed. Prentice Hall, Inc...research effort provides an adequate enough representation of the imaging process that any observed effects are not manufactured by the digital ...Fundamentals of Digital Image Processing . Prentice Hall, Inc., Englewood Cliffs, NJ. [30] Lampkin, Curt M., G.W. Flint, and M.J. MacFarlane (1988

  14. Local Environment and Interactions of Liquid and Solid Interfaces Revealed by Spectral Line Shape of Surface Selective Nonlinear Vibrational Probe

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Shun-Li; Fu, Li; Chase, Zizwe A.; Gan, Wei; Wang, Hong-Fei

    2016-11-10

    Vibrational spectral lineshape contains important detailed information of molecular vibration and reports its specific interactions and couplings to its local environment. In this work, recently developed sub-1 cm-1 high-resolution broadband sum frequency generation vibrational spectroscopy (HR-BB-SFG-VS) was used to measure the -C≡N stretch vibration in the 4-n-octyl-4’-cyanobiphenyl (8CB) Langmuir or Langmuir-Blodgett (LB) monolayer as a unique vibrational probe, and the spectral lineshape analysis revealed the local environment and interactions at the air/water, air/glass, air/calcium fluoride and air/-quartz interfaces for the first time. The 8CB Langmuir or LB film is uniform and the vibrational spectral lineshape of its -C≡N group has been well characterized, making it a good choice as the surface vibrational probe. Lineshape analysis of the 8CB -C≡N stretch SFG vibrational spectra suggests the coherent vibrational dynamics and the structural and dynamic inhomogeneity of the -C≡N group at each interface are uniquely different. In addition, it is also found that there are significantly different roles for water molecules in the LB films on different substrate surfaces. These results demonstrated the novel capabilities of the surface nonlinear spectroscopy in characterization and in understanding the specific structures and chemical interactions at the liquid and solid interfaces in general.

  15. Imaging theory of nonlinear second harmonic and third harmonic generations in confocal microscopy

    Institute of Scientific and Technical Information of China (English)

    TANG; Zhilie; XING; Da; LIU; Songhao

    2004-01-01

    The imaging theory of nonlinear second harmonic generation (SHG) and third harmonic generation (THG) in confocal microscopy is presented in this paper. The nonlinear effect of SHG and THG on the imaging properties of confocal microscopy has been analyzed in detail by the imaging theory. It is proved that the imaging process of SHG and THG in confocal microscopy, which is different from conventional coherent imaging or incoherent imaging, can be divided into two different processes of coherent imaging. The three-dimensional point spread functions (3D-PSF) of SHG and THG confocal microscopy are derived based on the nonlinear principles of SHG and THG. The imaging properties of SHG and THG confocal microscopy are discussed in detail according to its 3D-PSF. It is shown that the resolution of SHG and THG confocal microscopy is higher than that of single-and two-photon confocal microscopy.

  16. MARS spectral molecular imaging of lamb tissue: data collection and image analysis

    CERN Document Server

    Aamir, R; Bateman, C.J.; Butler, A.P.H.; Butler, P.H.; Anderson, N.G.; Bell, S.T.; Panta, R.K.; Healy, J.L.; Mohr, J.L.; Rajendran, K.; Walsh, M.F.; Ruiter, N.de; Gieseg, S.P.; Woodfield, T.; Renaud, P.F.; Brooke, L.; Abdul-Majid, S.; Clyne, M.; Glendenning, R.; Bones, P.J.; Billinghurst, M.; Bartneck, C.; Mandalika, H.; Grasset, R.; Schleich, N.; Scott, N.; Nik, S.J.; Opie, A.; Janmale, T.; Tang, D.N.; Kim, D.; Doesburg, R.M.; Zainon, R.; Ronaldson, J.P.; Cook, N.J.; Smithies, D.J.; Hodge, K.

    2014-01-01

    Spectral molecular imaging is a new imaging technique able to discriminate and quantify different components of tissue simultaneously at high spatial and high energy resolution. Our MARS scanner is an x-ray based small animal CT system designed to be used in the diagnostic energy range (20 to 140 keV). In this paper, we demonstrate the use of the MARS scanner, equipped with the Medipix3RX spectroscopic photon-processing detector, to discriminate fat, calcium, and water in tissue. We present data collected from a sample of lamb meat including bone as an illustrative example of human tissue imaging. The data is analyzed using our 3D Algebraic Reconstruction Algorithm (MARS-ART) and by material decomposition based on a constrained linear least squares algorithm. The results presented here clearly show the quantification of lipid-like, water-like and bone-like components of tissue. However, it is also clear to us that better algorithms could extract more information of clinical interest from our data. Because we ...

  17. Jeffries Matusita based mixed-measure for improved spectral matching in hyperspectral image analysis

    Science.gov (United States)

    Padma, S.; Sanjeevi, S.

    2014-10-01

    This paper proposes a novel hyperspectral matching technique by integrating the Jeffries-Matusita measure (JM) and the Spectral Angle Mapper (SAM) algorithm. The deterministic Spectral Angle Mapper and stochastic Jeffries-Matusita measure are orthogonally projected using the sine and tangent functions to increase their spectral ability. The developed JM-SAM algorithm is implemented in effectively discriminating the landcover classes and cover types in the hyperspectral images acquired by PROBA/CHRIS and EO-1 Hyperion sensors. The reference spectra for different land-cover classes were derived from each of these images. The performance of the proposed measure is compared with the performance of the individual SAM and JM approaches. From the values of the relative spectral discriminatory probability (RSDPB) and relative discriminatory entropy value (RSDE), it is inferred that the hybrid JM-SAM approach results in a high spectral discriminability than the SAM and JM measures. Besides, the use of the improved JM-SAM algorithm for supervised classification of the images results in 92.9% and 91.47% accuracy compared to 73.13%, 79.41%, and 85.69% of minimum-distance, SAM and JM measures. It is also inferred that the increased spectral discriminability of JM-SAM measure is contributed by the JM distance. Further, it is seen that the proposed JM-SAM measure is compatible with varying spectral resolutions of PROBA/CHRIS (62 bands) and Hyperion (242 bands).

  18. Hyperspectral Image Classification Based on the Weighted Probabilistic Fusion of Multiple Spectral-spatial Features

    Directory of Open Access Journals (Sweden)

    ZHANG Chunsen

    2015-08-01

    Full Text Available A hyperspectral images classification method based on the weighted probabilistic fusion of multiple spectral-spatial features was proposed in this paper. First, the minimum noise fraction (MNF approach was employed to reduce the dimension of hyperspectral image and extract the spectral feature from the image, then combined the spectral feature with the texture feature extracted based on gray level co-occurrence matrix (GLCM, the multi-scale morphological feature extracted based on OFC operator and the end member feature extracted based on sequential maximum angle convex cone (SMACC method to form three spectral-spatial features. Afterwards, support vector machine (SVM classifier was used for the classification of each spectral-spatial feature separately. Finally, we established the weighted probabilistic fusion model and applied the model to fuse the SVM outputs for the final classification result. In order to verify the proposed method, the ROSIS and AVIRIS image were used in our experiment and the overall accuracy reached 97.65% and 96.62% separately. The results indicate that the proposed method can not only overcome the limitations of traditional single-feature based hyperspectral image classification, but also be superior to conventional VS-SVM method and probabilistic fusion method. The classification accuracy of hyperspectral images was improved effectively.

  19. Application of Computed Tomography Virtual Noncontrast Spectral Imaging in Evaluation of Hepatic Metastases: A Preliminary Study

    Institute of Scientific and Technical Information of China (English)

    Shi-Feng Tian; Ai-Lian Liu; Jing-Hong Liu; Mei-Yu Sun; He-Qing Wang; Yi-Jun Liu

    2015-01-01

    Objective:The objective was to qualitatively and quantitatively evaluate hepatic metastases using computed tomography (CT) virtual noncontrast (VNC) spectral imaging in a retrospective analysis.Methods:Forty hepatic metastases patients underwent CT scans including the conventional true noncontrast (TNC) and the tri-phasic contrast-enhanced dual energy spectral scans in the hepatic arterial,portal venous,and equilibrium phases.The tri-phasic spectral CT images were used to obtain three groups of VNC images including in the arterial (VNCa),venous (VNCv),and equilibrium (VNCe) phase by the material decomposition process using water and iodine as a base material pair.The image quality and the contrast-to-noise ratio (CNR) of metastasis of the four groups were compared with ANOVA analysis.The metastasis detection rates with the four nonenhanced image groups were calculated and compared using the Chi-square test.Results:There were no significant differences in image quality among TNC,VNCa and VNCv images (P > 0.05).The quality of VNCe images was significantly worse than that of other three groups (P < 0.05).The mean CNR of metastasis in the TNC and VNCs images was 1.86,2.42,1.92,and 1.94,respectively; the mean CNR of metastasis in VNCa images was significantly higher than that in other three groups (P < 0.05),while no statistically significant difference was observed among VNCv,VNCe and TNC images (P > 0.05).The metastasis detection rate of the four nonenhanced groups with no statistically significant difference (P > 0.05).Conclusions:The quality of VNCa and VNCv images is identical to that of TNC images,and the metastasis detection rate in VNC images is similar to that in TNC images.VNC images obtained from arterial phase show metastases more clearly.Thus,VNCa imaging may be a surrogate to TNC imaging in hepatic metastasis diagnosis.

  20. Wide-angle spectral imaging using a Fabry-Perot interferometer

    NARCIS (Netherlands)

    Strauch, M.; Livshits, I.L.; Bociort, F.; Urbach, H.P.

    2015-01-01

    We show that wide-angle spectral imaging can be achieved with compact and cost-effective devices using Fabry-Pérot interferometers. Designs with a full field of view of 90°, in which the Fabry-Pérot interferometer is mounted either in front of an imaging lens system or behind a telecentric lens syst

  1. Ultrasound-guided spectral photoacoustic imaging of hemoglobin oxygenation during development

    Science.gov (United States)

    Bayer, Carolyn L.; Wlodarczyk, Bogdan J.; Finnell, Richard H.; Emelianov, Stanislav Y.

    2017-01-01

    Few technologies are capable of imaging in vivo function during development. In this study, we have implemented spectral photoacoustic imaging to estimate tissue oxygenation longitudinally in pregnant mice. We used the spectral photoacoustic signal to estimate hemoglobin oxygen saturation within intact, in vivo mouse concepti from developmental day (E) 8.5 to E16.5—a first step towards functional imaging of the maternal-fetal environment. Future work will apply these methods to compare longitudinal functional changes during normal vs abnormal development of embryos, fetuses, and placentas. PMID:28270982

  2. Experimental research on showing automatic disappearance pen handwriting based on spectral imaging technology

    Science.gov (United States)

    Su, Yi; Xu, Lei; Liu, Ningning; Huang, Wei; Xu, Xiaojing

    2016-10-01

    Purpose to find an efficient, non-destructive examining method for showing the disappearing words after writing with automatic disappearance pen. Method Using the imaging spectrometer to show the potential disappearance words on paper surface according to different properties of reflection absorbed by various substances in different bands. Results the disappeared words by using different disappearance pens to write on the same paper or the same disappearance pen to write on different papers, both can get good show results through the use of the spectral imaging examining methods. Conclusion Spectral imaging technology can show the disappearing words after writing by using the automatic disappearance pen.

  3. Delineation of subsurface hydrocarbon contamination at a former hydrogenation plant using spectral induced polarization imaging.

    Science.gov (United States)

    Flores Orozco, Adrián; Kemna, Andreas; Oberdörster, Christoph; Zschornack, Ludwig; Leven, Carsten; Dietrich, Peter; Weiss, Holger

    2012-08-01

    Broadband spectral induced polarization (SIP) measurements were conducted at a former hydrogenation plant in Zeitz (NE Germany) to investigate the potential of SIP imaging to delineate areas with different BTEX (benzene, toluene, ethylbenzene, and xylene) concentrations. Conductivity images reveal a poor correlation with the distribution of contaminants; whereas phase images exhibit two main anomalies: low phase shift values (1.7 g/l), and higher phase values for lower BTEX concentrations. Moreover, the spectral response of the areas with high BTEX concentration and free-phase products reveals a flattened spectrum in the low frequencies (contaminants at BTEX contaminated sites. Copyright © 2012 Elsevier B.V. All rights reserved.

  4. Hyperspectral Image Classification Based on the Combination of Spatial-spectral Feature and Sparse Representation

    Directory of Open Access Journals (Sweden)

    YANG Zhaoxia

    2015-07-01

    Full Text Available In order to avoid the problem of being over-dependent on high-dimensional spectral feature in the traditional hyperspectral image classification, a novel approach based on the combination of spatial-spectral feature and sparse representation is proposed in this paper. Firstly, we extract the spatial-spectral feature by reorganizing the local image patch with the first d principal components(PCs into a vector representation, followed by a sorting scheme to make the vector invariant to local image rotation. Secondly, we learn the dictionary through a supervised method, and use it to code the features from test samples afterwards. Finally, we embed the resulting sparse feature coding into the support vector machine(SVM for hyperspectral image classification. Experiments using three hyperspectral data show that the proposed method can effectively improve the classification accuracy comparing with traditional classification methods.

  5. Spectral characterization of acousto-optic filters used in imaging spectroscopy.

    Science.gov (United States)

    Georgiev, Georgi; Glenar, David A; Hillman, John J

    2002-01-01

    The purpose of this investigation is to improve the study of the characteristics of noncollinear acoustooptic tunable filters (AOTFs) used in imaging spectroscopy. Three filters were characterized and the results compared with tuning models to verify that device operation can be reliably predicted in advance. All these devices use tellurium dioxide as the interaction medium and have large geometric apertures for spectroscopic imaging applications in the spectral range 0.5-3.5 microm. The device characteristics that we studied were compared with the results of AOTF models, and the spectral and angular dependence of acoustic frequency and bandpass width for both output polarization states were confirmed by measurements. One of the AOTFs was used as a dispersive element coupled to external imaging optics. We summarize measurements of the basic spectral and imaging characteristics in this configuration.

  6. Dual Modality Noncontact Photoacoustic and Spectral Domain OCT Imaging.

    Science.gov (United States)

    Leiss-Holzinger, Elisabeth; Bauer-Marschallinger, Johannes; Hochreiner, Armin; Hollinger, Philipp; Berer, Thomas

    2016-01-01

    We developed a multimodal imaging system, combining noncontact photoacoustic imaging and optical coherence tomography (OCT). Photoacoustic signals are recorded without contact to the specimens' surface by using an interferometric technique. The interferometer is realized within a fiber-optic network using a fiber laser at 1550 nm as source. The fiber-optic network allows the integration of a fiber-based OCT system operating at a wavelength region around 1310 nm. Light from the fiber laser and the OCT source are multiplexed into one fiber using wavelength-division multiplexing. The same focusing optics is used for both modalities. Back-reflected light from the sample is demultiplexed and guided to the respective imaging systems. As the same optical components are used for OCT and photoacoustic imaging, the obtained images are co-registered intrinsically in lateral direction. Three-dimensional imaging is implemented by hybrid galvanometer and mechanical scanning. To allow fast B-scan measurements, scanning of the interrogation beam along one dimension is executed by a galvanometer scanner. Slow-axis scanning, perpendicular to the fast axis, is performed utilizing a linear translational stage. We demonstrate two-dimensional and three-dimensional imaging on agarose phantoms.

  7. Mitigation of nonlinear effects through frequency shift free mid-span spectral inversion using counter-propagating dual pumped FWM in fiber

    Science.gov (United States)

    Anchal, Abhishek; Kumar, Pradeep; Landais, Pascal

    2016-10-01

    We propose and numerically verify a scheme of frequency-shift free mid-span spectral inversion (MSSI) for nonlinearity mitigation in an optical transmission system. Spectral inversion is accomplished by optical phase conjugation, realized by counter-propagating dual pumped four-wave mixing in a highly nonlinear fiber. We examine the performance of MSSI due to critical parameters such as nonlinear fiber length, pump and signal power. We demonstrate the near complete nonlinearity mitigation of 40 Gbps DQPSK modulated data transmitted over 1000 km standard single mode fiber using our method of MSSI. We perform simulation of bit-error rate as a function of optical signal to noise ratio to corroborate the effect of frequency-shift free MSSI.

  8. A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images

    Directory of Open Access Journals (Sweden)

    Yi Wang

    2016-11-01

    Full Text Available Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is investigated. For a given hyperspectral image, the principle component analysis (PCA transform is first performed. Then, the first principle component of the input image is segmented into non-overlapping homogeneous regions by using the entropy rate superpixel (ERS algorithm. Next, the local spectral histogram model is applied to each homogeneous region to obtain the corresponding texture features. Because this step is performed within each homogenous region, instead of within a fixed-size image window, the obtained local texture features in the image are more accurate, which can effectively benefit the improvement of classification accuracy. In the following step, a contextual spectral-texture kernel is constructed by combining spectral information in the image and the extracted texture information using the linearity property of the kernel methods. Finally, the classification map is achieved by the support vector machines (SVM classifier using the proposed spectral-texture kernel. Experiments on two benchmark airborne hyperspectral datasets demonstrate that our method can effectively improve classification accuracies, even though only a very limited training sample is available. Specifically, our method can achieve from 8.26% to 15.1% higher in terms of overall accuracy than the traditional SVM classifier. The performance of our method was further compared to several state-of-the-art classification methods of hyperspectral images using objective quantitative measures and a visual qualitative evaluation.

  9. Determining Spectral Reflectance Coefficients from Hyperspectral Images Obtained from Low Altitudes

    Science.gov (United States)

    Walczykowski, P.; Jenerowicz, A.; Orych, A.; Siok, K.

    2016-06-01

    Remote Sensing plays very important role in many different study fields, like hydrology, crop management, environmental and ecosystem studies. For all mentioned areas of interest different remote sensing and image processing techniques, such as: image classification (object and pixel- based), object identification, change detection, etc. can be applied. Most of this techniques use spectral reflectance coefficients as the basis for the identification and distinction of different objects and materials, e.g. monitoring of vegetation stress, identification of water pollutants, yield identification, etc. Spectral characteristics are usually acquired using discrete methods such as spectrometric measurements in both laboratory and field conditions. Such measurements however can be very time consuming, which has led many international researchers to investigate the reliability and accuracy of using image-based methods. According to published and ongoing studies, in order to acquire these spectral characteristics from images, it is necessary to have hyperspectral data. The presented article describes a series of experiments conducted using the push-broom Headwall MicroHyperspec A-series VNIR. This hyperspectral scanner allows for registration of images with more than 300 spectral channels with a 1.9 nm spectral bandwidth in the 380- 1000 nm range. The aim of these experiments was to establish a methodology for acquiring spectral reflectance characteristics of different forms of land cover using such sensor. All research work was conducted in controlled conditions from low altitudes. Hyperspectral images obtained with this specific type of sensor requires a unique approach in terms of post-processing, especially radiometric correction. Large amounts of acquired imagery data allowed the authors to establish a new post- processing approach. The developed methodology allowed the authors to obtain spectral reflectance coefficients from a hyperspectral sensor mounted on an

  10. DETERMINING SPECTRAL REFLECTANCE COEFFICIENTS FROM HYPERSPECTRAL IMAGES OBTAINED FROM LOW ALTITUDES

    Directory of Open Access Journals (Sweden)

    P. Walczykowski

    2016-06-01

    Full Text Available Remote Sensing plays very important role in many different study fields, like hydrology, crop management, environmental and ecosystem studies. For all mentioned areas of interest different remote sensing and image processing techniques, such as: image classification (object and pixel- based, object identification, change detection, etc. can be applied. Most of this techniques use spectral reflectance coefficients as the basis for the identification and distinction of different objects and materials, e.g. monitoring of vegetation stress, identification of water pollutants, yield identification, etc. Spectral characteristics are usually acquired using discrete methods such as spectrometric measurements in both laboratory and field conditions. Such measurements however can be very time consuming, which has led many international researchers to investigate the reliability and accuracy of using image-based methods. According to published and ongoing studies, in order to acquire these spectral characteristics from images, it is necessary to have hyperspectral data. The presented article describes a series of experiments conducted using the push-broom Headwall MicroHyperspec A-series VNIR. This hyperspectral scanner allows for registration of images with more than 300 spectral channels with a 1.9 nm spectral bandwidth in the 380- 1000 nm range. The aim of these experiments was to establish a methodology for acquiring spectral reflectance characteristics of different forms of land cover using such sensor. All research work was conducted in controlled conditions from low altitudes. Hyperspectral images obtained with this specific type of sensor requires a unique approach in terms of post-processing, especially radiometric correction. Large amounts of acquired imagery data allowed the authors to establish a new post- processing approach. The developed methodology allowed the authors to obtain spectral reflectance coefficients from a hyperspectral sensor

  11. Spectral segmentation of polygonized images with normalized cuts

    Energy Technology Data Exchange (ETDEWEB)

    Matsekh, Anna [Los Alamos National Laboratory; Skurikhin, Alexei [Los Alamos National Laboratory; Rosten, Edward [UNIV OF CAMBRIDGE

    2009-01-01

    We analyze numerical behavior of the eigenvectors corresponding to the lowest eigenvalues of the generalized graph Laplacians arising in the Normalized Cuts formulations of the image segmentation problem on coarse polygonal grids.

  12. In vivo spectral micro-imaging of tissue

    Science.gov (United States)

    Demos, Stavros G; Urayama, Shiro; Lin, Bevin; Saroufeem, Ramez; Ghobrial, Moussa

    2012-11-27

    In vivo endoscopic methods an apparatuses for implementation of fluorescence and autofluorescence microscopy, with and without the use of exogenous agents, effectively (with resolution sufficient to image nuclei) visualize and categorize various abnormal tissue forms.

  13. Multi-objective based spectral unmixing for hyperspectral images

    Science.gov (United States)

    Xu, Xia; Shi, Zhenwei

    2017-02-01

    Sparse hyperspectral unmixing assumes that each observed pixel can be expressed by a linear combination of several pure spectra in a priori library. Sparse unmixing is challenging, since it is usually transformed to a NP-hard l0 norm based optimization problem. Existing methods usually utilize a relaxation to the original l0 norm. However, the relaxation may bring in sensitive weighted parameters and additional calculation error. In this paper, we propose a novel multi-objective based algorithm to solve the sparse unmixing problem without any relaxation. We transform sparse unmixing to a multi-objective optimization problem, which contains two correlative objectives: minimizing the reconstruction error and controlling the endmember sparsity. To improve the efficiency of multi-objective optimization, a population-based randomly flipping strategy is designed. Moreover, we theoretically prove that the proposed method is able to recover a guaranteed approximate solution from the spectral library within limited iterations. The proposed method can directly deal with l0 norm via binary coding for the spectral signatures in the library. Experiments on both synthetic and real hyperspectral datasets demonstrate the effectiveness of the proposed method.

  14. Spectral Mixture Analysis: Linear and Semi-parametric Full and Iterated Partial Unmixing in Multi- and Hyperspectral Image Data

    DEFF Research Database (Denmark)

    Nielsen, Allan Aasbjerg

    2001-01-01

    to suggest an iterated CEM scheme. Also the target constrained interference minimized filter (TCIMF) is described. Spectral angle mapping (SAM) is briefly described. Finally, semi-parametric unmixing (SPU) based on a combined linear and additive model with a non-linear, smooth function to represent end......As a supplement or an alternative to classification of hyperspectral image data linear and semi-parametric mixture models are considered in order to obtain estimates of abundance of each class or end-member in pixels with mixed membership. Full unmixing based on both ordinary least squares (OLS......) and non-negative least squares (NNLS), and the partial unmixing methods orthogonal subspace projection (OSP), constrained energy minimization (CEM) and an eigenvalue formulation alternative are dealt with. The solution to the eigenvalue formulation alternative proves to be identical to the CEM solution...

  15. A quaternion-based spectral clustering method for color image segmentation

    Science.gov (United States)

    Li, Xiang; Jin, Lianghai; Liu, Hong; He, Zeng

    2011-11-01

    Spectral clustering method has been widely used in image segmentation. A key issue in spectral clustering is how to build the affinity matrix. When it is applied to color image segmentation, most of the existing methods either use Euclidean metric to define the affinity matrix, or first converting color-images into gray-level images and then use the gray-level images to construct the affinity matrix (component-wise method). However, it is known that Euclidean distances can not represent the color differences well and the component-wise method does not consider the correlation between color channels. In this paper, we propose a new method to produce the affinity matrix, in which the color images are first represented in quaternion form and then the similarities between color pixels are measured by quaternion rotation (QR) mechanism. The experimental results show the superiority of the new method.

  16. Design and preliminary performance evaluation of airborne hyper-spectral imaging spectograph Air-OPUS

    Science.gov (United States)

    Okumura, Shin-ichiro; Suzuki, Makoto; Yoshida, Shigeomi; Sano, Takuki; Watanabe, Masaharu; Ogawa, Toshihiro

    2003-06-01

    Air-OPUS is a hyper spectral imaging spectrograph, with 0.34 nm spectral step, 190-455 nm spectral coverage, and 330 spatial channels covering 15 degrees field of view (FOV). It is designed as an airborne instrument for the demonstration of spaceborne-OPUS. After two-demonstration campaign using the Gulfstream-II aircraft, the performances of AIR-OPUS, such as spectral resolution, signal-to-noise ration (SNR) have been evaluated. It is concluded that the performances have agreed with designed value. This paper describes design, the performance, and the first results of Air-OPUS. Concept of next generation Air-OPUS, with wider FOV and visible/near-IR spectral coverage, will be also briefly presented.

  17. Non-linearly weighted fuzzy correlation for color-image retrieval

    Institute of Scientific and Technical Information of China (English)

    Guoguang Mu(母国光); Hongchen Zhai(翟宏琛); Siyuan Zhang(张思远)

    2003-01-01

    An algorithm with non-linear weight factors in the summation process for fuzzy correlation of color his-tograms is presented, in which non-linear weights are assigned to some characteristic colors of interest.Experimental results show that this can improve the retrieval of color images with partial aberrations orwith local color characters.

  18. Time of Flight Image Segmentation through Co-Regularized Spectral Clustering

    OpenAIRE

    Lorenti, Luciano; Giacomantone, Javier

    2014-01-01

    Time of Flight (TOF) cameras generate two simultaneous images, one for intensity and one for range. This allows tackling segmentation problems where the information pertaining to intensity or range alone is not enough to extract objects of interest from a 3D scene. In this paper, we present a spectral segmentation method that combines information from both images. By modifying the affinity matrix of each of the images based on the other, the segmentation of objects in the scene is improved. T...

  19. Compression of 1030-nm femtosecond pulses after nonlinear spectral broadening in Corning® HI 1060 fiber: Theory and experiment

    Directory of Open Access Journals (Sweden)

    Michael E. Reilly

    2015-12-01

    Full Text Available We present the design and implementation of femtosecond pulse compression at 1030 nm based on spectral broadening in single-mode fiber, followed by dispersion compensation using an optimized double-pass SF11 prism pair. The source laser produced 1030-nm 144-fs pulses which were coupled into Corning® HI 1060 fiber, whose length was chosen to be 40 cm by using a pulse propagation model based on solving the generalized nonlinear Schrödinger equation. A maximum broadening to 60-nm bandwidth was obtained, following which compression to 60 ± 3 fs duration was achieved by using a prism-pair separation of 1025 ± 5 mm.

  20. Analyses of spectral efficiency and nonlinear tolerance of DPSK formats in 160-Gb/s Raman amplified systems

    DEFF Research Database (Denmark)

    Xu, Zhenbo; Rottwitt, Karsten; Jeppesen, Palle

    2005-01-01

    Five-channel 160-Gb/s wavelength-division-multiplexing (WDM) systems using ABA dispersion map and Raman amplification are investigated numerically. Transmission distance and system margin are evaluated for return-to-zero differential phase-shift keying (RZ-DPSK) and carrier-suppressed return......-to-zero (CSRZ)-DPSK formats. The results show that RZ-DPSK can offer 2300-km system reach at large WDM channel spacing, while CSRZ-DPSK is more robust against nonlinear effects in the fibers and offers a reach of 1900 km at a spectral efficiency of 0.53 b/s/Hz. CSRZ-DPSK can also provide twice the dispersion...

  1. Interventional multi-spectral photoacoustic imaging in laparoscopic surgery

    Science.gov (United States)

    Hill, Emma R.; Xia, Wenfeng; Nikitichev, Daniil I.; Gurusamy, Kurinchi; Beard, Paul C.; Hawkes, David J.; Davidson, Brian R.; Desjardins, Adrien E.

    2016-03-01

    Laparoscopic procedures can be an attractive treatment option for liver resection, with a shortened hospital stay and reduced morbidity compared to open surgery. One of the central challenges of this technique is visualisation of concealed structures within the liver, particularly the vasculature and tumourous tissue. As photoacoustic (PA) imaging can provide contrast for haemoglobin in real time, it may be well suited to guiding laparoscopic procedures in order to avoid inadvertent trauma to vascular structures. In this study, a clinical laparoscopic ultrasound probe was used to receive ultrasound for PA imaging and to obtain co-registered B-mode ultrasound (US) images. Pulsed excitation light was delivered to the tissue via a fibre bundle in dark-field mode. Monte Carlo simulations were performed to optimise the light delivery geometry for imaging targets at depths of 1 cm, 2 cm and 3 cm, and 3D-printed mounts were used to position the fibre bundle relative to the transducer according to the simulation results. The performance of the photoacoustic laparoscope system was evaluated with phantoms and tissue models. The clinical potential of hybrid PA/US imaging to improve the guidance of laparoscopic surgery is discussed.

  2. EXISTENCE AND UNIQUENESS OF WEAK SOLUTIONS FOR A NONLINEAR PARABOLIC EQUATION RELATED TO IMAGE ANALYSIS

    Institute of Scientific and Technical Information of China (English)

    Wang Lihe; Zhou Shulin

    2006-01-01

    In this paper we establish the existence and uniqueness of weak solutions for the initial-boundary value problem of a nonlinear parabolic partial differential equation, which is related to the Malik-Perona model in image analysis.

  3. Contextual kernel and spectral methods for learning the semantics of images.

    Science.gov (United States)

    Lu, Zhiwu; Ip, Horace H S; Peng, Yuxin

    2011-06-01

    This paper presents contextual kernel and spectral methods for learning the semantics of images that allow us to automatically annotate an image with keywords. First, to exploit the context of visual words within images for automatic image annotation, we define a novel spatial string kernel to quantify the similarity between images. Specifically, we represent each image as a 2-D sequence of visual words and measure the similarity between two 2-D sequences using the shared occurrences of s -length 1-D subsequences by decomposing each 2-D sequence into two orthogonal 1-D sequences. Based on our proposed spatial string kernel, we further formulate automatic image annotation as a contextual keyword propagation problem, which can be solved very efficiently by linear programming. Unlike the traditional relevance models that treat each keyword independently, the proposed contextual kernel method for keyword propagation takes into account the semantic context of annotation keywords and propagates multiple keywords simultaneously. Significantly, this type of semantic context can also be incorporated into spectral embedding for refining the annotations of images predicted by keyword propagation. Experiments on three standard image datasets demonstrate that our contextual kernel and spectral methods can achieve significantly better results than the state of the art.

  4. Nonlinear dynamical systems of mathematical physics spectral and symplectic integrability analysis

    CERN Document Server

    Blackmore, Denis; Samoylenko, Valeriy Hr

    2011-01-01

    This distinctive volume presents a clear, rigorous grounding in modern nonlinear integrable dynamics theory and applications in mathematical physics, and an introduction to timely leading-edge developments in the field - including some innovations by the authors themselves - that have not appeared in any other book. The exposition begins with an introduction to modern integrable dynamical systems theory, treating such topics as Liouville-Arnold and Mischenko-Fomenko integrability. This sets the stage for such topics as new formulations of the gradient-holonomic algorithm for Lax integrability,

  5. Superpixel-based spectral classification for the detection of head and neck cancer with hyperspectral imaging

    Science.gov (United States)

    Chung, Hyunkoo; Lu, Guolan; Tian, Zhiqiang; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

    2016-03-01

    Hyperspectral imaging (HSI) is an emerging imaging modality for medical applications. HSI acquires two dimensional images at various wavelengths. The combination of both spectral and spatial information provides quantitative information for cancer detection and diagnosis. This paper proposes using superpixels, principal component analysis (PCA), and support vector machine (SVM) to distinguish regions of tumor from healthy tissue. The classification method uses 2 principal components decomposed from hyperspectral images and obtains an average sensitivity of 93% and an average specificity of 85% for 11 mice. The hyperspectral imaging technology and classification method can have various applications in cancer research and management.

  6. MULTIPLE REFLECTION EFFECTS IN NONLINEAR MIXTURE MODEL FOR HYPERSPECTRAL IMAGE ANALYSIS

    OpenAIRE

    Liu, C. Y.; Ren, H.

    2016-01-01

    Hyperspectral spectrometers can record electromagnetic energy with hundreds or thousands of spectral channels. With such high spectral resolution, the spectral information has better capability for material identification. Because of the spatial resolution, one pixel in hyperspectral images usually covers several meters, and it may contain more than one material. Therefore, the mixture model must be considered. Linear mixture model (LMM) has been widely used for remote sensing target...

  7. Liquid crystal-based Mueller matrix spectral imaging polarimetry for parameterizing mineral structural organization.

    Science.gov (United States)

    Gladish, James C; Duncan, Donald D

    2017-01-20

    Herein, we discuss the remote assessment of the subwavelength organizational structure of a medium. Specifically, we use spectral imaging polarimetry, as the vector nature of polarized light enables it to interact with optical anisotropies within a medium, while the spectral aspect of polarization is sensitive to small-scale structure. The ability to image these effects allows for inference of spatial structural organization parameters. This work describes a methodology for revealing structural organization by exploiting the Stokes/Mueller formalism and by utilizing measurements from a spectral imaging polarimeter constructed from liquid crystal variable retarders and a liquid crystal tunable filter. We provide results to validate the system and then show results from measurements on a mineral sample.

  8. An adaptive reconstruction algorithm for spectral CT regularized by a reference image

    Science.gov (United States)

    Wang, Miaoshi; Zhang, Yanbo; Liu, Rui; Guo, Shuxu; Yu, Hengyong

    2016-12-01

    The photon counting detector based spectral CT system is attracting increasing attention in the CT field. However, the spectral CT is still premature in terms of both hardware and software. To reconstruct high quality spectral images from low-dose projections, an adaptive image reconstruction algorithm is proposed that assumes a known reference image (RI). The idea is motivated by the fact that the reconstructed images from different spectral channels are highly correlated. If a high quality image of the same object is known, it can be used to improve the low-dose reconstruction of each individual channel. This is implemented by maximizing the patch-wise correlation between the object image and the RI. Extensive numerical simulations and preclinical mouse study demonstrate the feasibility and merits of the proposed algorithm. It also performs well for truncated local projections, and the surrounding area of the region- of-interest (ROI) can be more accurately reconstructed. Furthermore, a method is introduced to adaptively choose the step length, making the algorithm more feasible and easier for applications.

  9. Efficient single-pixel multispectral imaging via non-mechanical spatio-spectral modulation

    Science.gov (United States)

    Li, Ziwei; Suo, Jinli; Hu, Xuemei; Deng, Chao; Fan, Jingtao; Dai, Qionghai

    2017-01-01

    Combining spectral imaging with compressive sensing (CS) enables efficient data acquisition by fully utilizing the intrinsic redundancies in natural images. Current compressive multispectral imagers, which are mostly based on array sensors (e.g, CCD or CMOS), suffer from limited spectral range and relatively low photon efficiency. To address these issues, this paper reports a multispectral imaging scheme with a single-pixel detector. Inspired by the spatial resolution redundancy of current spatial light modulators (SLMs) relative to the target reconstruction, we design an all-optical spectral splitting device to spatially split the light emitted from the object into several counterparts with different spectrums. Separated spectral channels are spatially modulated simultaneously with individual codes by an SLM. This no-moving-part modulation ensures a stable and fast system, and the spatial multiplexing ensures an efficient acquisition. A proof-of-concept setup is built and validated for 8-channel multispectral imaging within 420~720 nm wavelength range on both macro and micro objects, showing a potential for efficient multispectral imager in macroscopic and biomedical applications.

  10. Color Restoration of RGBN Multispectral Filter Array Sensor Images Based on Spectral Decomposition.

    Science.gov (United States)

    Park, Chulhee; Kang, Moon Gi

    2016-05-18

    A multispectral filter array (MSFA) image sensor with red, green, blue and near-infrared (NIR) filters is useful for various imaging applications with the advantages that it obtains color information and NIR information simultaneously. Because the MSFA image sensor needs to acquire invisible band information, it is necessary to remove the IR cut-offfilter (IRCF). However, without the IRCF, the color of the image is desaturated by the interference of the additional NIR component of each RGB color channel. To overcome color degradation, a signal processing approach is required to restore natural color by removing the unwanted NIR contribution to the RGB color channels while the additional NIR information remains in the N channel. Thus, in this paper, we propose a color restoration method for an imaging system based on the MSFA image sensor with RGBN filters. To remove the unnecessary NIR component in each RGB color channel, spectral estimation and spectral decomposition are performed based on the spectral characteristics of the MSFA sensor. The proposed color restoration method estimates the spectral intensity in NIR band and recovers hue and color saturation by decomposing the visible band component and the NIR band component in each RGB color channel. The experimental results show that the proposed method effectively restores natural color and minimizes angular errors.

  11. Spectral Imaging for Revealing and Preserving World Cultural Heritage

    Science.gov (United States)

    2011-09-01

    characterization of manuscripts” Symposium on Digital Imaging of Ancient Textual Heritage, Helsinki, Finland, 2010, pp. 51-64. [4] R. L. Easton et. al...America, Giles, London, United Kingdom, 2008. 5. CONCLUSION [6] E. Harris , “The Waldseemüller Map – A typographic ap- praisal” Imago Mundi, Vol. 37

  12. Growth, spectral, linear and nonlinear optical characteristics of an efficient semiorganic acentric crystal: L-valinium L-valine chloride

    Science.gov (United States)

    Nageshwari, M.; Jayaprakash, P.; Kumari, C. Rathika Thaya; Vinitha, G.; Caroline, M. Lydia

    2017-04-01

    An efficient nonlinear optical semiorganic material L-valinium L-valine chloride (LVVCl) was synthesized and grown-up by means of slow evaporation process. Single crystal XRD evince that LVVCl corresponds to monoclinic system having acentric space group P21. The diverse functional groups existing in LVVCl were discovered with FTIR spectral investigation. The UV-Visible and photoluminescence spectrum discloses the optical and electronic properties respectively for the grown crystal. Several optical properties specifically extinction coefficient, reflectance, linear refractive index, electrical and optical conductivity were also determined. The SEM analysis was also carried out and it portrayed the surface morphology of LVVCl. The calculated value of laser damage threshold was 2.59 GW/cm2. The mechanical and dielectric property of LVVCl was investigated employing microhardness and dielectric studies. The second and third order nonlinear optical characteristics of LVVCl was characterized utilizing Kurtz Perry and Z scan technique respectively clearly suggest its suitability in the domain of optics and photonics.

  13. Grid Size Selection for Nonlinear Least-Squares Optimization in Spectral Estimation and Array Processing

    DEFF Research Database (Denmark)

    Nielsen, Jesper Kjær; Jensen, Tobias Lindstrøm; Jensen, Jesper Rindom;

    2016-01-01

    time. Additionally, we show via three common examples how the grid size depends on parameters such as the number of data points or the number of sensors in DOA estimation. We also demonstrate that the computation time can potentially be lowered by several orders of magnitude by combining a coarse grid......In many spectral estimation and array processing problems, the process of finding estimates of model parameters often involves the optimisation of a cost function containing multiple peaks and dips. Such non-convex problems are hard to solve using traditional optimisation algorithms developed...

  14. Spectral Methods for Linear and Non-Linear Semi-Supervised Dimensionality Reduction

    CERN Document Server

    Chatpatanasiri, Ratthachat

    2008-01-01

    We present a general framework of spectral methods for semi-supervised dimensionality reduction. Applying an approach called manifold regularization, our framework naturally generalizes existent supervised frameworks. Furthermore, by our two semi-supervised versions of the representer theorem, our framework can be kernelized as well. Using our framework, we give three examples of semi-supervised algorithms which are extended from three recent supervised algorithms, namely, ``discriminant neighborhood embedding'', ``marginal Fisher analysis'' and ``local Fisher discriminant analysis''. We also give three more semi-supervised examples of the kernel versions of these algorithms. Numerical results of the six semi-supervised algorithms compared to their supervised versions are presented.

  15. New method for nonlinear and nonstationary time series analysis: empirical mode decomposition and Hilbert spectral analysis

    Science.gov (United States)

    Huang, Norden E.

    2000-04-01

    A new method for analyzing nonlinear and nonstationary data has been developed. The key pat of the method is the Empirical Mode Decomposition method with which any complicated data set can be decomposed into a finite and often small number of Intrinsic Mode Functions (IMF). An IMF is define das any function having the same numbers of zero- crossing and extrema, and also having symmetric envelopes defined by the local maxima and minima respectively. The IMF also admits well-behaved Hilbert transform. This decomposition method is adaptive, and therefore, highly efficient. Since the decomposition is based on the local characteristic time scale of het data, it is applicable to nonlinear and nonstationary processes. With the Hilbert transform, the IMF yield instantaneous frequencies as functions of time that give sharp identifications of embedded structures. The final presentation of the result is an energy-frequency-time distribution, designated as the Hilbert Spectrum. Comparisons with Wavelet and window Fourier analysis show the new method offers much better temporal and frequency resolutions.

  16. Digital simulation of staining in histopathology multispectral images: enhancement and linear transformation of spectral transmittance.

    Science.gov (United States)

    Bautista, Pinky A; Yagi, Yukako

    2012-05-01

    Hematoxylin and eosin (H&E) stain is currently the most popular for routine histopathology staining. Special and/or immuno-histochemical (IHC) staining is often requested to further corroborate the initial diagnosis on H&E stained tissue sections. Digital simulation of staining (or digital staining) can be a very valuable tool to produce the desired stained images from the H&E stained tissue sections instantaneously. We present an approach to digital staining of histopathology multispectral images by combining the effects of spectral enhancement and spectral transformation. Spectral enhancement is accomplished by shifting the N-band original spectrum of the multispectral pixel with the weighted difference between the pixel's original and estimated spectrum; the spectrum is estimated using M transformed to the spectral configuration associated to its reaction to a specific stain by utilizing an N × N transformation matrix, which is derived through application of least mean squares method to the enhanced and target spectral transmittance samples of the different tissue components found in the image. Results of our experiments on the digital conversion of an H&E stained multispectral image to its Masson's trichrome stained equivalent show the viability of the method.

  17. Simultaneous iterative reconstruction technique software for spectral-spatial EPR imaging

    Science.gov (United States)

    Spitzbarth, Martin; Drescher, Malte

    2015-08-01

    Continuous wave electron paramagnetic resonance imaging (EPRI) experiments often suffer from low signal to noise ratio. The increase in spectrometer time required to acquire data of sufficient quality to allow further analysis can be counteracted in part by more processing effort during the image reconstruction step. We suggest a simultaneous iterative reconstruction algorithm (SIRT) for reconstruction of continuous wave EPRI experimental data as an alternative to the widely applied filtered back projection algorithm (FBP). We show experimental and numerical test data of 2d spatial images and spectral-spatial images. We find that for low signal to noise ratio and spectral-spatial images that are limited by the maximum magnetic field gradient strength SIRT is more suitable than FBP.

  18. Spectral-spatial hyperspectral image classification using super-pixel-based spatial pyramid representation

    Science.gov (United States)

    Fan, Jiayuan; Tan, Hui Li; Toomik, Maria; Lu, Shijian

    2016-10-01

    Spatial pyramid matching has demonstrated its power for image recognition task by pooling features from spatially increasingly fine sub-regions. Motivated by the concept of feature pooling at multiple pyramid levels, we propose a novel spectral-spatial hyperspectral image classification approach using superpixel-based spatial pyramid representation. This technique first generates multiple superpixel maps by decreasing the superpixel number gradually along with the increased spatial regions for labelled samples. By using every superpixel map, sparse representation of pixels within every spatial region is then computed through local max pooling. Finally, features learned from training samples are aggregated and trained by a support vector machine (SVM) classifier. The proposed spectral-spatial hyperspectral image classification technique has been evaluated on two public hyperspectral datasets, including the Indian Pines image containing 16 different agricultural scene categories with a 20m resolution acquired by AVIRIS and the University of Pavia image containing 9 land-use categories with a 1.3m spatial resolution acquired by the ROSIS-03 sensor. Experimental results show significantly improved performance compared with the state-of-the-art works. The major contributions of this proposed technique include (1) a new spectral-spatial classification approach to generate feature representation for hyperspectral image, (2) a complementary yet effective feature pooling approach, i.e. the superpixel-based spatial pyramid representation that is used for the spatial correlation study, (3) evaluation on two public hyperspectral image datasets with superior image classification performance.

  19. [The linear hyperspectral camera rotating scan imaging geometric correction based on the precise spectral sampling].

    Science.gov (United States)

    Wang, Shu-min; Zhang, Ai-wu; Hu, Shao-xing; Wang, Jing-meng; Meng, Xian-gang; Duan, Yi-hao; Sun, Wei-dong

    2015-02-01

    As the rotation speed of ground based hyperspectral imaging system is too fast in the image collection process, which exceeds the speed limitation, there is data missed in the rectified image, it shows as the_black lines. At the same time, there is serious distortion in the collected raw images, which effects the feature information classification and identification. To solve these problems, in this paper, we introduce the each component of the ground based hyperspectral imaging system at first, and give the general process of data collection. The rotation speed is controlled in data collection process, according to the image cover area of each frame and the image collection speed of the ground based hyperspectral imaging system, And then the spatial orientation model is deduced in detail combining with the star scanning angle, stop scanning angle and the minimum distance between the sensor and the scanned object etc. The oriented image is divided into grids and resampled with new spectral. The general flow of distortion image corrected is presented in this paper. Since the image spatial resolution is different between the adjacent frames, and in order to keep the highest image resolution of corrected image, the minimum ground sampling distance is employed as the grid unit to divide the geo-referenced image. Taking the spectral distortion into account caused by direct sampling method when the new uniform grids and the old uneven grids are superimposed to take the pixel value, the precise spectral sampling method based on the position distribution is proposed. The distortion image collected in Lao Si Cheng ruin which is in the Zhang Jiajie town Hunan province is corrected through the algorithm proposed on above. The features keep the original geometric characteristics. It verifies the validity of the algorithm. And we extract the spectral of different features to compute the correlation coefficient. The results show that the improved spectral sampling method is

  20. Identification of high explosive RDX using terahertz imaging and spectral fingerprints

    Science.gov (United States)

    Liu, Jia; Fan, Wen-Hui; Chen, Xu; Xie, Jun

    2016-01-01

    We experimentally investigated the spectral fingerprints of high explosive cyclo-1,3,5- trimethylene-2,4,6-trinitramine (RDX) in terahertz frequency region. A home-made terahertz time-domain spectroscopy ranging from 0.2 THz∼ 3.4 THz was deployed. Furthermore, two sample pellets (RDX pellet and polyethylene pellet), which were concealed in an opaque envelop, could be identified by using terahertz pulse imaging system. For the purpose of distinguishing the RDX between two pellets, we further calculated the THz frequency -domain map using its spectral fingerprints. It is demonstrated that the high explosive RDX could similarly be identified using terahertz frequency-domain imaging.

  1. Multi spectral imaging analysis for meat spoilage discrimination

    DEFF Research Database (Denmark)

    Christiansen, Asger Nyman; Carstensen, Jens Michael; Papadopoulou, Olga

    ) was performed in parallel with videometer image snapshots and sensory analysis. Odour and colour characteristics of meat were determined by a test panel and attributed into three pre-characterized quality classes, namely Fresh; Semi Fresh and Spoiled during the days of its shelf life. So far, different...... classification methods: Naive Bayes Classifier as a reference model, Canonical Discriminant Analysis (CDA) and Support Vector Classification (SVC). As the final step, generalization of the models was performed using k-fold validation (k=10). Results showed that image analysis provided good discrimination of meat...... samples regarding the spoilage process as evaluated from sensory as well as from microbiological data. The support vector classification (SVC) model outperformed other models. Specifically, the misclassification error rate (MER), derived from odour characteristics, was 18% for both aerobic and MAP meat...

  2. Spectral imaging of breast fibroadenoma using second-harmonic generation

    Science.gov (United States)

    Zheng, Liqin; Wang, Yuhua

    2014-09-01

    Fibroadenoma (FA), typically composed of stroma and epithelial cells, is a very common benign breast disease. Women with FA are associated with an increased risk of future breast cancer. The objective of this study was to demonstrate the potential of multiphoton laser scanning microscopy (MPLSM) for characterizing the morphology of collagen in the human breast fibroadenomas. In the study, high-contrast SHG images of human normal breast tissues and fibroadenoma tissues were obtained for comparison. The morphology of collagen was different between normal breast tissue and fibroadenoma. This study shows that MPLSM has the ability to distinguish fibroadenoma tissues from the normal breast tissues based on the noninvasive SHG imaging. With the advent of the clinical portability of miniature MPLSM, we believe that the technique has great potential to be used in vivo studies and for monitoring the treatment responses of fibroadenomas in clinical.

  3. REMOTE SPECTRAL IMAGING USING A LOW COST UAV SYSTEM

    Directory of Open Access Journals (Sweden)

    C. Tsouvaltsidis

    2015-08-01

    Full Text Available The purpose of this scientific survey is to support the research being conducted at York University in the field of spectroscopy and nanosatellites using Argus 1000 micro- spectrometer and low cost unmanned aerial vehicle (UAV system. On the CanX-2 mission, the Argus spectrometer observes reflected infrared solar radiation emitted by Earth surface targets as small as 1.5 km within the 0.9-1.7 μm range. However, limitations in the volume of data due to onboard power constraints and a lack of an onboard camera system make it very difficult to verify these objectives using ground truth. In the last five years that Argus has been in operation, we have made over 200 observations over a series of land and ocean targets. We have recently examined algorithms to improve the geolocation accuracy of the spectrometer payload and began to conduct an analysis of soil health content using Argus spectral data. A field campaign is used to obtain data to assess geolocation accuracy using coastline crossing detection and to obtain airborne bare soil spectra in ground truth form. The payload system used for the field campaign consists of an Argus spectrometer, optical camera, GPS, and attitude sensors, integrated into a low-cost, unmanned aerial vehicle (UAV, which will be presented along with the experimental procedure and field campaign results.

  4. Characterization of Lunar Soils Using a Thermal Infrared Microscopic Spectral Imaging System

    Science.gov (United States)

    Crites, S. T.; Lucey, P. G.

    2010-12-01

    Lunar Reconnaissance Orbiter's Diviner radiometer has provided the planetary science community with a large amount of thermal infrared spectral data. This data set offers rich opportunities for lunar science, but interpretation of the data is complicated by the limited data on lunar materials. While spectra of pure terrestrial minerals have been used effectively for Mars applications, lunar minerals and glasses have been affected by space weathering processes that may alter their spectral properties in important ways. For example, mineral grains acquire vapor deposited coatings, and agglutinate glass contains abundant nanophase iron as a result of exposure to the space environment. Producing mineral separates in sufficient quantities (at least tens of mg) for spectral characterization is painstaking, time consuming and labor intensive; as an alternative we have altered an infrared hyperspectral imaging system developed for remote sensing under funding from the Planetary Instrument Definition and Development program (PIDDP) to enable resolved microscopic spectral imaging. The concept is to characterize the spectral properties of individual grains in lunar soils, enabling a wide range of spectral behaviors of components to be measured rapidly. The instrument, sensitive from 8 to 15 microns at 15 wavenumber resolution, images a field of view of 8 millimeters at 30 micron resolution and scans at a rate of about 1 mm/second enabling relatively large areas to be scanned rapidly. Our experiments thus far use a wet-sieved 90-150 um size fraction with the samples arrayed on a heated substrate in a single layer in order to prevent spectral interactions between grains. We have begun with pure mineral separates, and unsurprisingly we find that the individual mineral grain emission spectra of a wide range of silicates are very similar to spectra of coarse grained powders. We have begun to obtain preliminary data on lunar soils as well. We plan to continue imaging of lunar soils

  5. High-resolution fiber optic temperature sensors using nonlinear spectral curve fitting technique

    Science.gov (United States)

    Su, Z. H.; Gan, J.; Yu, Q. K.; Zhang, Q. H.; Liu, Z. H.; Bao, J. M.

    2013-04-01

    A generic new data processing method is developed to accurately calculate the absolute optical path difference of a low-finesse Fabry-Perot cavity from its broadband interference fringes. The method combines Fast Fourier Transformation with nonlinear curve fitting of the entire spectrum. Modular functions of LabVIEW are employed for fast implementation of the data processing algorithm. The advantages of this technique are demonstrated through high performance fiber optic temperature sensors consisting of an infrared superluminescent diode and an infrared spectrometer. A high resolution of 0.01 °C is achieved over a large dynamic range from room temperature to 800 °C, limited only by the silica fiber used for the sensor.

  6. ANALYZING SPECTRAL CHARACTERISTICS OF SHADOW AREA FROM ADS-40 HIGH RADIOMETRIC RESOLUTION AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    Y.-T. Hsieh

    2016-06-01

    Full Text Available The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i The DN values in shadow area are much lower than in nonshadow area; (ii DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv The shadow area NIR of vegetation category also shows a strong reflection; (v Generally, vegetation indexes (NDVI still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40 is potential for the extract land cover information of shadow areas.

  7. Analyzing Spectral Characteristics of Shadow Area from ADS-40 High Radiometric Resolution Aerial Images

    Science.gov (United States)

    Hsieh, Yi-Ta; Wu, Shou-Tsung; Chen, Chaur-Tzuhn; Chen, Jan-Chang

    2016-06-01

    The shadows in optical remote sensing images are regarded as image nuisances in numerous applications. The classification and interpretation of shadow area in a remote sensing image are a challenge, because of the reduction or total loss of spectral information in those areas. In recent years, airborne multispectral aerial image devices have been developed 12-bit or higher radiometric resolution data, including Leica ADS-40, Intergraph DMC. The increased radiometric resolution of digital imagery provides more radiometric details of potential use in classification or interpretation of land cover of shadow areas. Therefore, the objectives of this study are to analyze the spectral properties of the land cover in the shadow areas by ADS-40 high radiometric resolution aerial images, and to investigate the spectral and vegetation index differences between the various shadow and non-shadow land covers. According to research findings of spectral analysis of ADS-40 image: (i) The DN values in shadow area are much lower than in nonshadow area; (ii) DN values received from shadowed areas that will also be affected by different land cover, and it shows the possibility of land cover property retrieval as in nonshadow area; (iii) The DN values received from shadowed regions decrease in the visible band from short to long wavelengths due to scattering; (iv) The shadow area NIR of vegetation category also shows a strong reflection; (v) Generally, vegetation indexes (NDVI) still have utility to classify the vegetation and non-vegetation in shadow area. The spectral data of high radiometric resolution images (ADS-40) is potential for the extract land cover information of shadow areas.

  8. Optical Doppler tomography and spectral Doppler imaging of localized ischemic stroke in a mouse model

    Science.gov (United States)

    Yu, Lingfeng; Nguyen, Elaine; Liu, Gangjun; Rao, Bin; Choi, Bernard; Chen, Zhongping

    2010-02-01

    We present a combined optical Doppler tomography/spectral Doppler imaging modality to quantitatively evaluate the dynamic blood circulation and the artery blockage before and after a localized ischemic stroke in a mouse model. Optical Doppler Tomography (ODT) combines the Doppler principle with optical coherence tomography for noninvasive localization and measurement of particle flow velocity in highly scattering media with micrometer scale spatial resolution. Spectral Doppler imaging (SDI) provides complementary temporal flow information to the spatially distributed flow information of Doppler imaging. Fast, repeated, ODT scans across an entire vessel were performed to record flow dynamic information with high temporal resolution of cardiac cycles. Spectral Doppler analysis of continuous Doppler images demonstrates how the velocity components and longitudinally projected flow-volume-rate change over time for scatters within the imaging volume using spectral Doppler waveforms. Furthermore, vascular conditions can be quantified with various Doppler-angle-independent flow indices. Non-invasive in-vivo mice experiments were performed to evaluate microvascular blood circulation of a localized ischemic stroke mouse model.

  9. Image quality assessment method based on nonlinear feature extraction in kernel space

    Institute of Scientific and Technical Information of China (English)

    Yong DING‡; Nan LI; Yang ZHAO; Kai HUANG

    2016-01-01

    To match human perception, extracting perceptual features effectively plays an important role in image quality assessment. In contrast to most existing methods that use linear transformations or models to represent images, we employ a complex mathematical expression of high dimensionality to reveal the statistical characteristics of the images. Furthermore, by introducing kernel methods to transform the linear problem into a nonlinear one, a full-reference image quality assessment method is proposed based on high-dimensional nonlinear feature extraction. Experiments on the LIVE, TID2008, and CSIQ databases demonstrate that nonlinear features offer competitive performance for image inherent quality representation and the proposed method achieves a promising performance that is consistent with human subjective evaluation.

  10. Simultaneous Spectral-Spatial Feature Selection and Extraction for Hyperspectral Images.

    Science.gov (United States)

    Zhang, Lefei; Zhang, Qian; Du, Bo; Huang, Xin; Tang, Yuan Yan; Tao, Dacheng

    2016-09-12

    In hyperspectral remote sensing data mining, it is important to take into account of both spectral and spatial information, such as the spectral signature, texture feature, and morphological property, to improve the performances, e.g., the image classification accuracy. In a feature representation point of view, a nature approach to handle this situation is to concatenate the spectral and spatial features into a single but high dimensional vector and then apply a certain dimension reduction technique directly on that concatenated vector before feed it into the subsequent classifier. However, multiple features from various domains definitely have different physical meanings and statistical properties, and thus such concatenation has not efficiently explore the complementary properties among different features, which should benefit for boost the feature discriminability. Furthermore, it is also difficult to interpret the transformed results of the concatenated vector. Consequently, finding a physically meaningful consensus low dimensional feature representation of original multiple features is still a challenging task. In order to address these issues, we propose a novel feature learning framework, i.e., the simultaneous spectral-spatial feature selection and extraction algorithm, for hyperspectral images spectral-spatial feature representation and classification. Specifically, the proposed method learns a latent low dimensional subspace by projecting the spectral-spatial feature into a common feature space, where the complementary information has been effectively exploited, and simultaneously, only the most significant original features have been transformed. Encouraging experimental results on three public available hyperspectral remote sensing datasets confirm that our proposed method is effective and efficient.

  11. 3D spectral imaging system for anterior chamber metrology

    Science.gov (United States)

    Anderson, Trevor; Segref, Armin; Frisken, Grant; Frisken, Steven

    2015-03-01

    Accurate metrology of the anterior chamber of the eye is useful for a number of diagnostic and clinical applications. In particular, accurate corneal topography and corneal thickness data is desirable for fitting contact lenses, screening for diseases and monitoring corneal changes. Anterior OCT systems can be used to measure anterior chamber surfaces, however accurate curvature measurements for single point scanning systems are known to be very sensitive to patient movement. To overcome this problem we have developed a parallel 3D spectral metrology system that captures simultaneous A-scans on a 2D lateral grid. This approach enables estimates of the elevation and curvature of anterior and posterior corneal surfaces that are robust to sample movement. Furthermore, multiple simultaneous surface measurements greatly improve the ability to register consecutive frames and enable aggregate measurements over a finer lateral grid. A key element of our approach has been to exploit standard low cost optical components including lenslet arrays and a 2D sensor to provide a path towards low cost implementation. We demonstrate first prototypes based on 6 Mpixel sensor using a 250 μm pitch lenslet array with 300 sample beams to achieve an RMS elevation accuracy of 1μm with 95 dB sensitivity and a 7.0 mm range. Initial tests on Porcine eyes, model eyes and calibration spheres demonstrate the validity of the concept. With the next iteration of designs we expect to be able to achieve over 1000 simultaneous A-scans in excess of 75 frames per second.

  12. Far ultraviolet imaging from the IMAGE spacecraft. 3. Spectral imaging of Lyman-α and OI 135.6 nm

    Science.gov (United States)

    Mende, S. B.; Heetderks, H.; Frey, H. U.; Stock, J. M.; Lampton, M.; Geller, S. P.; Abiad, R.; Siegmund, O. H. W.; Habraken, S.; Renotte, E.; Jamar, C.; Rochus, P.; Gerard, J.-C.; Sigler, R.; Lauche, H.

    2000-01-01

    Two FUV Spectral imaging instruments, the Spectrographic Imager (SI) and the Geocorona Photometer (GEO) provide IMAGE with simultaneous global maps of the hydrogen (121.8 nm) and oxygen 135.6 nm components of the terrestrial aurora and with observations of the three dimensional distribution of neutral hydrogen in the magnetosphere (121.6 nm). The SI is a novel instrument type, in which spectral separation and imaging functions are independent of each other. In this instrument, two-dimensional images are produced on two detectors, and the images are spectrally filtered by a spectrograph part of the instrument. One of the two detectors images the Doppler-shifted Lyman-α while rejecting the geocoronal `cold' Ly-α, and another detector images the OI 135.6 nm emission. The spectrograph is an all-reflective Wadsworth configuration in which a grill arrangement is used to block most of the cold, un-Doppler-shifted geocoronal emission at 121.567 nm. The SI calibration established that the upper limit of transmission at cold geocoronal Ly-α is less than 2%. The measured light collecting efficiency was 0.01 and 0.008 cm^2 at 121.8 and at 135.6 nm, respectively. This is consistent with the size of the input aperture, the optical transmission, and the photocathode efficiency. The expected sensitivity is 1.8x10^-2 and 1.3x10^-2 counts per Rayleigh per pixel for each 5 s viewing exposure per satellite revolution (120 s). The measured spatial resolution is better than the 128x128 pixel matrix over the 15 degx15 deg field of view in both wavelength channels. The SI detectors are photon counting devices using the cross delay line principle. In each detector a triple stack microchannel plate (MCP) amplifies the photo-electronic charge which is then deposited on a specially configured anode array. The position of the photon event is measured by digitizing the time delay between the pulses detected at each end of the anode structures. This scheme is intrinsically faster than systems

  13. Fast, cheap and in control: spectral imaging with handheld devices

    Science.gov (United States)

    Gooding, Edward A.; Deutsch, Erik R.; Huehnerhoff, Joseph; Hajian, Arsen R.

    2017-05-01

    Remote sensing has moved out of the laboratory and into the real world. Instruments using reflection or Raman imaging modalities become faster, cheaper and more powerful annually. Enabling technologies include virtual slit spectrometer design, high power multimode diode lasers, fast open-loop scanning systems, low-noise IR-sensitive array detectors and low-cost computers with touchscreen interfaces. High-volume manufacturing assembles these components into inexpensive portable or handheld devices that make possible sophisticated decision-making based on robust data analytics. Examples include threat, hazmat and narcotics detection; remote gas sensing; biophotonic screening; environmental remediation and a host of other applications.

  14. Image Retrieval Based on Multiview Constrained Nonnegative Matrix Factorization and Gaussian Mixture Model Spectral Clustering Method

    Directory of Open Access Journals (Sweden)

    Qunyi Xie

    2016-01-01

    Full Text Available Content-based image retrieval has recently become an important research topic and has been widely used for managing images from repertories. In this article, we address an efficient technique, called MNGS, which integrates multiview constrained nonnegative matrix factorization (NMF and Gaussian mixture model- (GMM- based spectral clustering for image retrieval. In the proposed methodology, the multiview NMF scheme provides competitive sparse representations of underlying images through decomposition of a similarity-preserving matrix that is formed by fusing multiple features from different visual aspects. In particular, the proposed method merges manifold constraints into the standard NMF objective function to impose an orthogonality constraint on the basis matrix and satisfy the structure preservation requirement of the coefficient matrix. To manipulate the clustering method on sparse representations, this paper has developed a GMM-based spectral clustering method in which the Gaussian components are regrouped in spectral space, which significantly improves the retrieval effectiveness. In this way, image retrieval of the whole database translates to a nearest-neighbour search in the cluster containing the query image. Simultaneously, this study investigates the proof of convergence of the objective function and the analysis of the computational complexity. Experimental results on three standard image datasets reveal the advantages that can be achieved with the proposed retrieval scheme.

  15. [Selection of interpolation methods used to mitigate spectral misregistration of imaging spectrometers].

    Science.gov (United States)

    Chen, Xu; Xiang, Yang; Feng, Yu-Tao

    2011-04-01

    Spectral curvature destroys the co-registration of the spectra measured by dispersion imaging spectrometer. Using interpolation to re-sample the measured spectra at the non-offset mid-wavelengths can mitigate the spectral misregistration. It is very important to select an optimum interpolation method. The performances of six common interpolation methods are evaluated by comparing the residual errors in the corrected spectral radiance. The results indicate that, four-point cubic Lagrange interpolation and cubic spline interpolation are better than other four interpolation methods (linear Interpolation, three points quadratic polynomial interpolation, five points four-order Lagrange interpolation and cubic Hermite interpolation). For spectral offset of 10% deltalambda (deltalambda = 5 nm), the normalized errors in measured spectral radiance is PV = 0.06, that is reduced to PV interpolation with cubic Lagrange interpolation or cubic spline interpolation, but for other four methods they are PV > 0.035. Furthermore, for lower spectral resolution (deltalambda > 5 nm), cubic Lagrange interpolation is a little better than cubic spline interpolation; while for higher spectral resolution (deltalambda interpolation is a little better.

  16. An Algorithm for In-Flight Spectral Calibration of Imaging Spectrometers

    Directory of Open Access Journals (Sweden)

    Gerrit Kuhlmann

    2016-12-01

    Full Text Available Accurate spectral calibration of satellite and airborne spectrometers is essential for remote sensing applications that rely on accurate knowledge of center wavelength (CW positions and slit function parameters (SFP. We present a new in-flight spectral calibration algorithm that retrieves CWs and SFPs across a wide spectral range by fitting a high-resolution solar spectrum and atmospheric absorbers to in-flight radiance spectra. Using a maximum a posteriori optimal estimation approach, the quality of the fit can be improved with a priori information. The algorithm was tested with synthetic spectra and applied to data from the APEX imaging spectrometer over the spectral range of 385–870 nm. CWs were retrieved with high accuracy (uncertainty <0.05 spectral pixels from Fraunhofer lines below 550 nm and atmospheric absorbers above 650 nm. This enabled a detailed characterization of APEX’s across-track spectral smile and a previously unknown along-track drift. The FWHMs of the slit function were also retrieved with good accuracy (<10% uncertainty for synthetic spectra, while some obvious misfits appear for the APEX spectra that are likely related to radiometric calibration issues. In conclusion, our algorithm significantly improves the in-flight spectral calibration of APEX and similar spectrometers, making them better suited for the retrieval of atmospheric and surface variables relying on accurate calibration.

  17. Investigations of OCT imaging performance using a unique source providing several spectral wavebands

    Science.gov (United States)

    Cernat, Ramona; Dobre, George M.; Trifanov, Irina; Neagu, Liviu; Bradu, Adrian; Hughes, Michael; Podoleanu, Adrian Gh.

    2008-02-01

    The authors report investigations into the suitability of a broadband supercontinuum fiber laser (SCFL) for use in Optical Coherence Tomography (OCT). The supercontinuum of light extending from 400 nm to 1800 nm can be used selectively in several spectral wavebands from 600 nm to 1700 nm in order to characterize the performance of single mode (SM) fiber OCT systems through spectral and auto-correlation measurements, dispersion measurements and image acquisition. Spectral selection and tailoring is made possible through a combination of bandpass optical filters. In addition, for the first time, given the optical bandwidth available, we perform evaluation of effective noise bandwidths which take into consideration the spectral behavior of the optical splitter in the balanced detection receiver.

  18. Classification of Error-Diffused Halftone Images Based on Spectral Regression Kernel Discriminant Analysis

    Directory of Open Access Journals (Sweden)

    Zhigao Zeng

    2016-01-01

    Full Text Available This paper proposes a novel algorithm to solve the challenging problem of classifying error-diffused halftone images. We firstly design the class feature matrices, after extracting the image patches according to their statistics characteristics, to classify the error-diffused halftone images. Then, the spectral regression kernel discriminant analysis is used for feature dimension reduction. The error-diffused halftone images are finally classified using an idea similar to the nearest centroids classifier. As demonstrated by the experimental results, our method is fast and can achieve a high classification accuracy rate with an added benefit of robustness in tackling noise.

  19. Segmentation of synthetic aperture radar image using multiscale information measure-based spectral clustering

    Institute of Scientific and Technical Information of China (English)

    Haixia Xu; Zheng Tian; Mingtao Ding

    2008-01-01

    @@ A multiscale information measure (MIM), calculable from per-pixel wavelet coefficients, but relying on global statistics of synthetic aperture radar (SAR) image, is proposed. It fully exploits the variations in speckle pattern when the image resolution varies from course to fine, thus it can capture the intrinsic texture of the scene backscatter and the texture due to speckle simultaneously. Graph spectral segmentation methods based on MIM and the usual similarity measure are carried out on two real SAR images.Experimental results show that MIM can characterize texture information of SAR image more effectively than the commonly used similarity measure.

  20. Dispersion management for controlling image plane in Fourier-domain spectrally encoded endoscopy.

    Science.gov (United States)

    Merman, Michal; Yelin, Dvir

    2011-02-28

    Spectrally encoded endoscopy (SEE) uses single optical fiber and miniature diffractive optics to allow imaging through a miniature probe. Utilizing Fourier-domain interferometry, SEE was shown capable of video-rate three-dimensional imaging, albeit at limited depth of field due to the limited spectral resolution of the detection spectrometer. We show that by using dispersion management at the reference arm of the interferometer, the tilt and curvature of the field of view could be adjusted without modifying the endoscopic probe itself. By controlling the group velocity dispersion, this technique is demonstrated useful for imaging specimen regions which reside outside the system's depth of field. This approach could be used to improve usability, functionality and image quality of SEE without affecting probe size and flexibility.

  1. Color Standardization Method and System for Whole Slide Imaging Based on Spectral Sensing

    Directory of Open Access Journals (Sweden)

    Shinsuke Tani

    2012-01-01

    Full Text Available In the field of whole slide imaging, the imaging device or staining process cause color variations for each slide that affect the result of image analysis made by pathologist. In order to stabilize the analysis, we developed a color standardization method and system as described below: 1 Color standardization method based on RGB imaging and multi spectral sensing, which utilize less band (16 bands than conventional method (60 bands, 2 High speed spectral sensing module. As a result, we confirmed the following effect: 1 We confirmed the performance improvement of nucleus detection by the color standardization. And we can conduct without training data set which is needed in conventional method, 2 We can get detection performance of H&E component equivalent to conventional method (60 bands. And measurement process is more than 255 times faster.

  2. Rapid mapping of digital integrated circuit logic gates via multi-spectral backside imaging

    CERN Document Server

    Adato, Ronen; Zangeneh, Mahmoud; Zhou, Boyou; Joshi, Ajay; Goldberg, Bennett; Unlu, M Selim

    2016-01-01

    Modern semiconductor integrated circuits are increasingly fabricated at untrusted third party foundries. There now exist myriad security threats of malicious tampering at the hardware level and hence a clear and pressing need for new tools that enable rapid, robust and low-cost validation of circuit layouts. Optical backside imaging offers an attractive platform, but its limited resolution and throughput cannot cope with the nanoscale sizes of modern circuitry and the need to image over a large area. We propose and demonstrate a multi-spectral imaging approach to overcome these obstacles by identifying key circuit elements on the basis of their spectral response. This obviates the need to directly image the nanoscale components that define them, thereby relaxing resolution and spatial sampling requirements by 1 and 2 - 4 orders of magnitude respectively. Our results directly address critical security needs in the integrated circuit supply chain and highlight the potential of spectroscopic techniques to addres...

  3. Automated, non-linear registration between 3-dimensional brain map and medical head image

    Energy Technology Data Exchange (ETDEWEB)

    Mizuta, Shinobu; Urayama, Shin-ichi; Zoroofi, R.A.; Uyama, Chikao [National Cardiovascular Center, Suita, Osaka (Japan)

    1998-05-01

    In this paper, we propose an automated, non-linear registration method between 3-dimensional medical head image and brain map in order to efficiently extract the regions of interest. In our method, input 3-dimensional image is registered into a reference image extracted from a brain map. The problems to be solved are automated, non-linear image matching procedure, and cost function which represents the similarity between two images. Non-linear matching is carried out by dividing the input image into connected partial regions, transforming the partial regions preserving connectivity among the adjacent images, evaluating the image similarity between the transformed regions of the input image and the correspondent regions of the reference image, and iteratively searching the optimal transformation of the partial regions. In order to measure the voxelwise similarity of multi-modal images, a cost function is introduced, which is based on the mutual information. Some experiments using MR images presented the effectiveness of the proposed method. (author)

  4. Chest CT using spectral filtration: radiation dose, image quality, and spectrum of clinical utility

    Energy Technology Data Exchange (ETDEWEB)

    Braun, Franziska M.; Johnson, Thorsten R.C.; Sommer, Wieland H.; Thierfelder, Kolja M.; Meinel, Felix G. [University Hospital Munich, Institute for Clinical Radiology, Munich (Germany)

    2015-06-01

    To determine the radiation dose, image quality, and clinical utility of non-enhanced chest CT with spectral filtration. We retrospectively analysed 25 non-contrast chest CT examinations acquired with spectral filtration (tin-filtered Sn100 kVp spectrum) compared to 25 examinations acquired without spectral filtration (120 kV). Radiation metrics were compared. Image noise was measured. Contrast-to-noise-ratio (CNR) and figure-of-merit (FOM) were calculated. Diagnostic confidence for the assessment of various thoracic pathologies was rated by two independent readers. Effective chest diameters were comparable between groups (P = 0.613). In spectral filtration CT, median CTDI{sub vol}, DLP, and size-specific dose estimate (SSDE) were reduced (0.46 vs. 4.3 mGy, 16 vs. 141 mGy*cm, and 0.65 vs. 5.9 mGy, all P < 0.001). Spectral filtration CT had higher image noise (21.3 vs. 13.2 HU, P < 0.001) and lower CNR (47.2 vs. 75.3, P < 0.001), but was more dose-efficient (FOM 10,659 vs. 2,231/mSv, P < 0.001). Diagnostic confidence for parenchymal lung disease and osseous pathologies was lower with spectral filtration CT, but no significant difference was found for pleural pathologies, pulmonary nodules, or pneumonia. Non-contrast chest CT using spectral filtration appears to be sufficient for the assessment of a considerable spectrum of thoracic pathologies, while providing superior dose efficiency, allowing for substantial radiation dose reduction. (orig.)

  5. Development of short-wavelength near-infrared spectral imaging for grain color classification

    Science.gov (United States)

    Archibald, Douglas D.; Thai, Chi N.; Dowell, Floyd E.

    1999-01-01

    Color class of wheat is an important attribute for the identification of cultivars and the marketing of wheat, but is not always easy to measure in the visible spectral range because of variation in vitreosity and surface structure of the kernels. This work examines whether short-wavelength near IR imaging in the range 632-1098 nm can be used to distinguish different cultivars. The spectral characteristics of six hard white winter and hard red spring wheats were first studied by bulk-sample SW-NIR reflectance spectroscopy using regression analysis to select appropriate wavelengths and sets of wavelengths. Prediction of percent red wheat was better if C-H or O-H vibrational overtones were included in the models in addition to the tail from the visible chromophore absorbance, apparently because the vibrational bands make it possible to normalize the color measurement to the dry matter content of the samples. Next, a reflectance spectral image of 640 X 480 spatial pixels and 11 wavelengths was acquired for a mixture of the two contrasting wheat samples using a CCD camera and a liquid crystal tunable filter. The cultivars were distinguished in the image of principal component (PC) score number two that was calculated from the spectral image. The discrimination is due to the tail from the absorbance band that peaks in the visible. PC images 3 and 6 seem to arise mainly from O-H and C-H bands, respectively, and it is speculated that these spectral features will be important for generating multivariate models to predict the color class of grain. It is shown that the contrast between the red-wheat, white- wheat and background can be increased by applying histogram equalization and segmentation of the kernels in the images.

  6. Incremental Classification Algorithm of Hyperspectral Remote Sensing Images Based on Spectral-spatial Information

    Directory of Open Access Journals (Sweden)

    WANG Junshu

    2015-09-01

    Full Text Available An incremental classification algorithm INC_SPEC_MPext was proposed for hyperspectral remote sensing images based on spectral and spatial information. The spatial information was extracted by building morphological profiles based on several principle components of hyperspectral image. The morphological profiles were combined together in extended morphological profiles (MPext. Combine spectral and MPext to enrich knowledge and utilize the useful information of unlabeled data at the most extent to optimize the classifier. Pick out high confidence data and add to training set, then retrain the classifier with augmented training set to predict the rest samples. The process was performed iteratively. The proposed algorithm was tested on AVIRIS Indian Pines and Hyperion EO-1 Botswana data, which take on different covers, and experimental results show low classification cost and significant improvements in terms of accuracies and Kappa coefficient under limited training samples compared with the classification results based on spectral, MPext and the combination of sepctral and MPext.

  7. Multiple irradiation sensing of the optical effective attenuation coefficient for spectral correction in handheld OA imaging

    Directory of Open Access Journals (Sweden)

    K. Gerrit Held

    2016-06-01

    Full Text Available Spectral optoacoustic (OA imaging enables spatially-resolved measurement of blood oxygenation levels, based on the distinct optical absorption spectra of oxygenated and de-oxygenated blood. Wavelength-dependent optical attenuation in the bulk tissue, however, distorts the acquired OA spectrum and thus makes quantitative oxygenation measurements challenging. We demonstrate a correction for this spectral distortion without requiring a priori knowledge of the tissue optical properties, using the concept of multiple irradiation sensing: recording the OA signal amplitude of an absorbing structure (e.g. blood vessel, which serves as an intrinsic fluence detector, as function of irradiation position. This permits the reconstruction of the bulk effective optical attenuation coefficient μeff,λ. If performed at various irradiation wavelengths, a correction for the wavelength-dependent fluence attenuation is achieved, revealing accurate spectral information on the absorbing structures. Phantom studies were performed to show the potential of this technique for handheld clinical combined OA and ultrasound imaging.

  8. Development of a new spectral library classifier for airborne hyperspectral images on heterogeneous environments

    OpenAIRE

    Mende, Andre; Heiden, Uta; Bachmann, Martin; Hoja, Danielle; Buchroithner, Manfred

    2011-01-01

    The classification of hyperspectral images on heterogeneous environments without prior knowledge about the study area is a challenging task. Finding potential pure spectral signatures or endmembers (EM) of the various surface materials within an image is essential for obtaining accurate classification results. Automated endmember selection techniques, in many cases, return an unlabelled result without a relationship to a known material. This study demonstrates the potential of an automated sp...

  9. Can Spectral CT Imaging Improve the Differentiation between Malignant and Benign Solitary Pulmonary Nodules?

    Science.gov (United States)

    Hua, Xiaolan; Yu, Mingji; Xu, Chengdong; Zhang, Feng; Xu, Jianrong; Wu, Huawei

    2016-01-01

    Purpose To quantitatively assess the value of dual-energy CT (DECT) in differentiating malignancy and benignity of solitary pulmonary nodules. Materials and Methods Sixty-three patients with solitary pulmonary nodules detected by CT plain scan underwent contrast enhanced CT scans in arterial phase (AP) and venous phase (VP) with spectral imaging mode for tumor type differentiation. The Gemstone Spectral Imaging (GSI) viewer was used for image display and data analysis. Region of interest was placed on the relatively homogeneous area of the nodule to measure iodine concentration (IC) on iodine-based material decomposition images and CT numbers on monochromatic image sets to generate spectral HU curve. Normalized IC (NIC), slope of the spectral HU curve (λHU) and net CT number enhancement on 70keV images were calculated. The two-sample t-test was used to compare quantitative parameters. Receiver operating characteristic curves were generated to calculate sensitivity and specificity. Results There were 63 nodules, with 37 malignant nodules (59%) and 26 benign nodules (41%). NIC, λHU and net CT number enhancement on 70keV images for malignant nodules were all greater than those of benign nodules. NIC and λHU had intermediate to high performances to differentiate malignant nodules from benign ones with the areas under curve of 0.89 and 0.86 respectively in AP, 0.96 and 0.89 respectively in VP. Using 0.30 as a threshold value for NIC in VP, one could obtain sensitivity of 93.8% and specificity of 85.7% for differentiating malignant from benign solitary pulmonary nodules. These values were statistically higher than the corresponding values of 74.2% and 53.8% obtained with the conventional CT number enhancement. Conclusions DECT imaging with GSI mode provides more promising value in quantitative way for distinguishing malignant nodules from benign ones than CT enhancement numbers. PMID:26840459

  10. Performance Evaluation of Machine Learning Algorithms for Urban Pattern Recognition from Multi-spectral Satellite Images

    OpenAIRE

    Marc Wieland; Massimiliano Pittore

    2014-01-01

    In this study, a classification and performance evaluation framework for the recognition of urban patterns in medium (Landsat ETM, TM and MSS) and very high resolution (WorldView-2, Quickbird, Ikonos) multi-spectral satellite images is presented. The study aims at exploring the potential of machine learning algorithms in the context of an object-based image analysis and to thoroughly test the algorithm’s performance under varying conditions to optimize their usage for urban pattern recognitio...

  11. Phase-sensitive imaging of tissue acoustic vibrations using spectrally encoded interferometry.

    Science.gov (United States)

    Ilgayev, Ovadia; Yelin, Dvir

    2013-08-26

    Acoustic vibrations in tissue are often difficult to image, requiring high-speed scanning, high sensitivity and nanometer-scale axial resolution. Here we use spectrally encoded interferometry to measure the vibration pattern of two-dimensional surfaces, including the skin of a volunteer, at nanometric resolution, without the need for rapid lateral scanning and with no prior knowledge of the driving acoustic waveform. Our results demonstrate the feasibility of this technique for measuring tissue biomechanics using simple and compact imaging probes.

  12. Can Spectral CT Imaging Improve the Differentiation between Malignant and Benign Solitary Pulmonary Nodules?

    Directory of Open Access Journals (Sweden)

    Ying Zhang

    Full Text Available To quantitatively assess the value of dual-energy CT (DECT in differentiating malignancy and benignity of solitary pulmonary nodules.Sixty-three patients with solitary pulmonary nodules detected by CT plain scan underwent contrast enhanced CT scans in arterial phase (AP and venous phase (VP with spectral imaging mode for tumor type differentiation. The Gemstone Spectral Imaging (GSI viewer was used for image display and data analysis. Region of interest was placed on the relatively homogeneous area of the nodule to measure iodine concentration (IC on iodine-based material decomposition images and CT numbers on monochromatic image sets to generate spectral HU curve. Normalized IC (NIC, slope of the spectral HU curve (λHU and net CT number enhancement on 70keV images were calculated. The two-sample t-test was used to compare quantitative parameters. Receiver operating characteristic curves were generated to calculate sensitivity and specificity.There were 63 nodules, with 37 malignant nodules (59% and 26 benign nodules (41%. NIC, λHU and net CT number enhancement on 70keV images for malignant nodules were all greater than those of benign nodules. NIC and λHU had intermediate to high performances to differentiate malignant nodules from benign ones with the areas under curve of 0.89 and 0.86 respectively in AP, 0.96 and 0.89 respectively in VP. Using 0.30 as a threshold value for NIC in VP, one could obtain sensitivity of 93.8% and specificity of 85.7% for differentiating malignant from benign solitary pulmonary nodules. These values were statistically higher than the corresponding values of 74.2% and 53.8% obtained with the conventional CT number enhancement.DECT imaging with GSI mode provides more promising value in quantitative way for distinguishing malignant nodules from benign ones than CT enhancement numbers.

  13. Quantum chemical computations and Fourier transform infrared spectral studies of a nonlinear food dye E110.

    Science.gov (United States)

    Snehalatha, M; Sekar, N; Jayakumar, V S; Joe, I Hubert

    2008-01-01

    Fourier transform infrared (FTIR) spectrum of a well-known food dye sunset yellow FCF (E110) has been recorded and analysed. Assignments of the vibrational spectrum has been facilitated by density functional theory (DFT) calculations. The results of the optimized molecular structure obtained on the basis of B3LYP with 6-31G(d) along with the 'LANL2DZ' basis sets give clear evidence for the intramolecular charge transfer (ICT) and strong hydrogen bonding enhancing the optical nonlinearity of the molecule. The first hyperpolarizability of the acidic monoazo dye 'E110' is computed. Azo stretching frequencies have been lowered due to conjugation and pi-electron delocalization. Hydroxyl vibrations with intramolecular H-bonding are analyzed, supported by the computed results. The natural bond orbitals (NBO) analysis confirms this strong hydrogen bond between the hydrogen of the hydroxyl group and nitrogen of the azo group of the molecule. Assignments of benzene and naphthalene ring vibrations are found to agree well with the theoretical wave numbers.

  14. NIR Capturing images with spectral information in the mid-infrared

    DEFF Research Database (Denmark)

    Dam, Jeppe Seidelin; Tidemand-Lichtenberg, Peter; Pedersen, Christian

    We demonstrate a method to capture images containing spectral information in the infrared. The method is based on sum frequency mixing of light, which allows for transformation of mid-infrared radiation to near visible light, allowing for use of a regular silicon based camera for detection. Combi...

  15. Raman spectral imaging technique on detection of melamine in skim milk powder

    Science.gov (United States)

    A point-scan Raman spectral imaging system was used for quantitative detection of melamine in milk powder. A sample depth of 2 mm and corresponding laser intensity of 200 mW were selected after evaluating the penetration of a 785 nm laser through milk powder. Horizontal and vertical spatial resoluti...

  16. Distant Determination of Bilirubin Distribution in Skin by Multi-Spectral Imaging

    Science.gov (United States)

    Saknite, I.; Jakovels, D.; Spigulis, J.

    2011-01-01

    For mapping the bilirubin distribution in bruised skin the multi-spectral imaging technique was employed, which made it possible to observe temporal changes of the bilirubin content in skin photo-types II and III. The obtained results confirm the clinical potential of this technique for skin bilirubin diagnostics.

  17. The performance of Dynamic Spectral Imaging colposcopy depends on indication for referrals

    NARCIS (Netherlands)

    Louwers, J. A.; Zaal, A.; Kocken, M.; Berkhof, J.; Papagiannakis, E.; Snijders, P. J. F.; Meijer, C. J. L. M.; Verheijen, RHM

    2015-01-01

    Objective. A previous study has shown that Dynamic Spectral Imaging (DSI) colposcopy increases the sensitivity of the colposcopic examination in women referred with abnormal cytology. In this study we have re-analyzed the performance of DSI and conventional colposcopy for new referral conditions and

  18. Study on Raman spectral imaging method for simultaneous estimation of ingredients concentration in food powder

    Science.gov (United States)

    This study investigated the potential of point scan Raman spectral imaging method for estimation of different ingredients and chemical contaminant concentration in food powder. Food powder sample was prepared by mixing sugar, vanillin, melamine and non-dairy cream at 5 different concentrations in a ...

  19. A spatial-spectral approach for deriving high signal quality eigenvectors for remote sensing image transformations

    DEFF Research Database (Denmark)

    Rogge, Derek; Bachmann, Martin; Rivard, Benoit

    2014-01-01

    -line surveys, or temporal data sets as computational burden becomes significant. In this paper we present a spatial-spectral approach to deriving high signal quality eigenvectors for image transformations which possess an inherently ability to reduce the effects of noise. The approach applies a spatial...

  20. Coupled nonlinear-diffusion color image sharpening based on the chromaticity-brightness model

    Science.gov (United States)

    Saito, Takahiro; Nosaka, Reina; Komatsu, Takashi

    2006-01-01

    Previously we have presented a selective image sharpening method based on the coupled nonlinear diffusion process composed of a nonlinear diffusion term, a fidelity term and an isotropic peaking term, and it can sharpen only blurred edges without increasing the noise visibility. Our previously presented prototypal color-image sharpening methods based on the coupled nonlinear-diffusion process have been formulated on the linear color models, namely, the channel-bychannel model and the 3D vectorial model. Our prototypal methods can sharpen blurred color step edges, but they do not necessarily enhance contrasts of signal variations in complex texture image regions so well as in simple step-edge regions. To remedy the drawback, this paper extends our coupled nonlinear-diffusion color-image sharpening method to the nonlinear non-flat color model, namely, the chromaticity-brightness model, which is known to be closely relating to human color perception. We modify our time-evolution PDE's for the non-flat space of the chromaticity vector and present its digital implementations. Through experimental simulations, we compare our new color-image sharpening method based on the chromaticity-brightness model with our prototypal color-image sharpening methods based on the linear color models.