Trade-off studies of a hyperspectral infrared sounder on a geostationary satellite

Trade-off studies on spectral coverage, signal-to-noise ratio (SNR), and spectral resolution for a hyperspectral infrared (IR) sounder on a geostationary satellite are summarized. The data density method is applied for the vertical resolution analysis, and the rms error between true and retrieved profiles is used to represent the retrieval accuracy. The effects of spectral coverage, SNR, and spectral resolution on vertical resolution and retrieval accuracy are investigated. The advantages of IR and microwave sounder synergy are also demonstrated. When focusing on instrument performance and data processing, the results from this study show that the preferred spectral coverage combines long-wave infrared (LWIR) with the shorter middle-wave IR (SMidW). Using the appropriate spectral coverage, a hyperspectral IR sounder with appropriate SNR can achieve the required science performance (1 km vertical resolution, 1 K temperature, and 10% relative humidity retrieval accuracy). The synergy of microwave and IR sounders can improve the vertical resolution and retrieval accuracy compared to either instrument alone.     

Adaptive affinity propagation with spectral angle mapper for semi-supervised hyperspectral band selection

Band selection is a commonly used approach for dimensionality reduction in hyperspectral imagery. Affinity propagation (AP), a new clustering algorithm, is addressed in many fields, and it can be used for hyperspectral band selection. However, this algorithm cannot get a fixed number of exemplars during the message-passing procedure, which limits its uses to a great extent. This paper proposes an adaptive AP (AAP) algorithm for semi-supervised hyperspectral band selection and investigates the effectiveness of distance metrics for improving band selection. Specifically, the exemplar number determination algorithm and bisection method are addressed to improve AP procedure, and the relations between selected exemplar numbers and preferences are established. Experiments are conducted to evaluate the proposed AAP-based band selection algorithm, and the results demonstrate that the proposed method outperforms other popular methods, with lower computational cost and robust results.     

Detection of gaseous plumes in IR hyperspectral images using hierarchical clustering

The emergence of IR hyperspectral sensors in recent years enables their use in remote environmental monitoring of gaseous plumes. IR hyperspectral imaging combines the unique advantages of traditional remote sensing methods such as multispectral imagery and nonimaging Fourier transform infrared spectroscopy, while eliminating their drawbacks. The most significant improvement introduced by hyperspectral technology is the capability of standoff detection and discrimination of effluent gaseous plumes without need for a clear reference background or any other temporal information. We introduce a novel approach for detection and discrimination of gaseous plumes in IR hyperspectral imagery using a divisive hierarchical clustering algorithm. The utility of the suggested detection algorithm is demonstrated on IR hyperspectral images of the release of two atmospheric tracers. The application of the proposed detection method on the experimental data has yielded a correct identification of all the releases without any false alarms. These encouraging results show that the presented approach can be used as a basis for a complete identification algorithm for gaseous pollutants in IR hyperspectral imagery without the need for a clear background.     

Lubrication approximation in completed double layer boundary element method

This paper reports on the results of the numerical simulation of the motion of solid spherical particles in shear Stokes flows. Using the completed double layer boundary element method (CDLBEM) via distributed computing under Parallel Virtual Machine (PVM), the effective viscosity of suspension has been calculated for a finite number of spheres in a cubic array, or in a random configuration. In the simulation presented here, the short range interactions via lubrication forces are also taken into account, via the range completer in the formulation, whenever the gap between two neighbouring particles is closer than a critical gap. The results for particles in a simple cubic array agree with the results of Nunan and Keller (1984) and Stoksian Dynamics of Brady et al. (1988). To evaluate the lubrication forces between particles in a random configuration, a critical gap of 0.2 of particle's radius is suggested and the results are tested against the experimental data of Thomas (1965) and empirical equation of Krieger-Dougherty (Krieger, 1972). Finally, the quasi-steady trajectories are obtained for time-varying configuration of 125 particles.     

Diffractive micro bar codes for encoding of biomolecules in multiplexed assays

Microparticles incorporating micrometer-sized diffractive bar codes have been modified with oligonucleotides and immunoglobulin Gs to enable DNA hybridization and immunoassays. The bar codes are manufactured using photolithography of a chemically functional commercial epoxy photoresist (SU-8). When attached by suitable linkers, immobilized probe molecules exhibit high affinity for analytes and fast reaction kinetics, allowing detection of single nucleotide differences in DNA sequences and multiplexed immunoassays in <45 min. Analysis of raw data from assays carried out on the diffractive microparticles indicates that the reproducibility and sensitivity approach those of commercial encoding platforms. Micrometer-sized particles, imprinted with several superimposed diffraction gratings, can encode many million unique codes. The high encoding capacity of this technology along with the applicability of the manufactured bar codes to multiplexed assays will allow accurate measurement of a wide variety of molecular interactions, leading to new opportunities in diverse areas of biotechnology such as genomics, proteomics, high-throughput screening, and medical diagnostics.     

Automated Deep Learning Driven Crop Classification on Hyperspectral Remote Sensing Images

Hyperspectral remote sensing/imaging spectroscopy is a novel approach to reaching a spectrum from all the places of a huge array of spatial places so that several spectral wavelengths are utilized for making coherent images. Hyperspectral remote sensing contains acquisition of digital images from several narrow, contiguous spectral bands throughout the visible, Thermal Infrared (TIR), Near Infrared (NIR), and Mid-Infrared (MIR) regions of the electromagnetic spectrum. In order to the application of agricultural regions, remote sensing approaches are studied and executed to their benefit of continuous and quantitative monitoring. Particularly, hyperspectral images (HSI) are considered the precise for agriculture as they can offer chemical and physical data on vegetation. With this motivation, this article presents a novel Hurricane Optimization Algorithm with Deep Transfer Learning Driven Crop Classification (HOADTL-CC) model on Hyperspectral Remote Sensing Images. The presented HOADTL-CC model focuses on the identification and categorization of crops on hyperspectral remote sensing images. To accomplish this, the presented HOADTL-CC model involves the design of HOA with capsule network (CapsNet) model for generating a set of useful feature vectors. Besides, Elman neural network (ENN) model is applied to allot proper class labels into the input HSI. Finally, glowworm swarm optimization (GSO) algorithm is exploited to fine tune the ENN parameters involved in this article. The experimental result scrutiny of the HOADTL-CC method can be tested with the help of benchmark dataset and the results are assessed under distinct aspects. Extensive comparative studies stated the enhanced performance of the HOADTL-CC model over recent approaches with maximum accuracy of 99.51%.     

基于矩阵模式的高光谱波段选择方法

去除冗余信息,进行特征提取是当前高光谱数据处理的一个重要课题。本文根据波段选择的基本准则,结合离散系数和相关系数对高光谱影像空间维和光谱维的可分性及相关性进行分析,提出了基于矩阵模式的高光谱波段选择方法-BSMM,并且定义了一个矩阵因子。在计算空间信息量时比较了标准差和离散系数的量化结果,除此之外,采用区间映射有效地消除了离散系数和相关系数变换区间不一致的情况。最后利用AVIRIS高光谱数据,通过与最佳指数因子的比较验证了该方法的有效性。     

基于光谱特征和纹理特征协同学习的高光谱图像数据分类

高光谱遥感图像中包含有大量的高维数据,传统的有监督学习算法在对这些数据进行分类时要求获取足够多的有标记样本用于分类器的训练.然而,对高光谱图像中大量的复杂地物像元所属类别进行准确标注通常需要耗费极大的人力.在本文中,我们提出了一种基于半监督学习的光谱和纹理特征协同学习(STF-CT)--法,利用协同学习机制将高光谱图像光谱特征和空间纹理特征这两种不同的特征结合起来,用于小训练样本集下的高光谱图像数据分类问题.STF-CT算法充分利用了高光谱图像的光谱和纹理特征这两个独立视图,构建起一种有效的半监督分类方法,用于提升分类器在小训练样本集情况下的分类精度.实验结果表明该算法在小训练样本集下的高光谱地物分类问题上具有很好的效果.     

Fe3O4/SiO2/CMCH/CdTe荧光磁性微球的合成与表征

利用St ber法和交联法制备出具有荧光和磁性功能的Fe3O4/SiO2/CMCH/CdTe微球,并对其性能和应用效果进行了分析讨论.首先以正硅酸四乙酯为前躯体,Fe2＋和Fe3＋物质的量的比为1∶2,利用超临界干燥法制备出了Fe3O4/SiO2复合微球;并通过透射电镜对其进行观察,Fe3O4颗粒粒径为10 nm,SiO2层厚度为5 nm;其次羧甲基化的壳聚糖（CMCH）被嫁接在Fe3O4/SiO2表面上;然后利用水热法制备出CdTe荧光颗粒,通过壳聚糖与CdTe之间的静电吸引作用,CdTe被吸附在壳聚糖表面;最后利用戊二醛对壳聚糖的选择性交联作用制备出粒径在200 nm以内,饱和磁化强度为22.16 A.m2/kg,且具有良好荧光性能的Fe3O4/SiO2/CMCH/CdTe微球.荧光光谱分析表明最大发射波长从519 nm红移到528 nm,也证实了荧光颗粒CdTe成功吸附在Fe3O4/SiO2/CMCH表面.在动物实验中,该复合微球也显示出良好的荧光性、磁性及稳定性.     

高光谱数据融合研究

多传感器的遥感数据融合在城市规划、土地利用、矿产探测、军事侦察等领域有着非常广泛的应用前景。本文高光谱图像光谱分辨率高、空间分辨率低、多光谱图像空间分辨率高、光谱分辨率高的特点,阐述了其数据融合。特别介绍了CRISP锐化算法。     

Automated target detection system for hyperspectral imaging sensors

Over the past several years, hyperspectral sensor technology has evolved to the point where real-time processing for operational applications is achievable. Algorithms supporting such sensors must be fully automated and robust. Our approach, for target detection applications, is to select signatures from a target reflectance library database and project them to the at-sensor and collection-specific radiance domain using the weather forecast or radiosonde data. This enables platform-based detection immediately following data acquisition without the need for further atmospheric compensation. One advantage of this method for reflective hyperspectral sensors is the ability to predict the radiance signatures of targets under multiple illumination conditions. A three-phase approach is implemented, where the library generation and data acquisition phases provide the necessary input for the automated detection phase. In addition to employing the target detector itself, this final phase includes a series of automated filters, adaptive thresholding, and confidence assignments to extract the optimal information from the detection scores for each spectral class. Our prototype software is applied to 50 reflective hyperspectral datacubes to measure detection performance over a range of targets, backgrounds, and environmental conditions.     

Quantifying the absorption and reduced scattering coefficients of tissuelike turbid media over a broad spectral range with noncontact Fourier-transform hyperspectral imaging

Absorption (mu(a)) and reduced scattering (mu(s)') spectra of turbid media were quantified with a noncontact imaging approach based on a Fourier-transform interferometric imaging system (FTIIS). The FTIIS was used to collect hyperspectral images of the steady-state diffuse reflectance from turbid media. Spatially resolved reflectance data from Monte Carlo simulations were fitted to the recorded hyperspectral images to quantify mu(a) and mu(s)' spectra in the 550-850-nm region. A simple and effective calibration approach was introduced to account for the instrument response. With reflectance data that were close to and far from the source (0.5-6.5 mm), mu(a) and mu(s)' of homogeneous, semi-infinite turbid phantoms with optical property ranges comparable with those of tissues were determined with an accuracy of +/-7% and +/-3%, respectively. Prediction accuracy for mu(a) and mu(s)' degraded to +/-12% and +/-4%, respectively, when only reflectance data close to the source (0.5-2.5 mm) were used. Results indicate that reflectance data close to and far from the source are necessary for optimal quantification of mu(a) and mu(s)'. The spectral properties of mu(a) and mu(s)' values were used to determine the concentrations of absorbers and scatterers, respectively. Absorber and scatterer concentrations of two-chromophore turbid media were determined with an accuracy of +/-5% and +/-3%, respectively.     

Hyperspectral remote sensing for shallow waters. 2. Deriving bottom depths and water properties by optimization

In earlier studies of passive remote sensing of shallow-water bathymetry, bottom depths were usually derived by empirical regression. This approach provides rapid data processing, but it requires knowledge of a few true depths for the regression parameters to be determined, and it cannot reveal in-water constituents. In this study a newly developed hyperspectral, remote-sensing reflectance model for shallow water is applied to data from computer simulations and field measurements. In the process, a remote-sensing reflectance spectrum is modeled by a set of values of absorption, backscattering, bottom albedo, and bottom depth; then it is compared with the spectrum from measurements. The difference between the two spectral curves is minimized by adjusting the model values in a predictor-corrector scheme. No information in addition to the measured reflectance is required. When the difference reaches a minimum, or the set of variables is optimized, absorption coefficients and bottom depths along with other properties are derived simultaneously. For computer-simulated data at a wind speed of 5 m/s the retrieval error was 5.3% for depths ranging from 2.0 to 20.0 m and 7.0% for total absorption coefficients at 440 nm ranging from 0.04 to 0.24 m(-1). At a wind speed of 10 m/s the errors were 5.1% for depth and 6.3% for total absorption at 440 nm. For field data with depths ranging from 0.8 to 25.0 m the difference was 10.9% (R(2) = 0.96, N = 37) between inversion-derived and field-measured depth values and just 8.1% (N = 33) for depths greater than 2.0 m. These results suggest that the model and the method used in this study, which do not require in situ calibration measurements, perform very well in retrieving in-water optical properties and bottom depths from above-surface hyperspectral measurements.     

基于BP网络的苹果硬度高光谱无损检测

目的为了实现基于高光谱成像以及误差反向传播(BP)网络模型的苹果硬度快速无损检测。方法利用高光谱成像采集系统采集采后"富士"苹果的高光谱图像,然后提取整个苹果样本区域的平均反射光谱;利用连续投影算法(SPA)和竞争性自适应重加权算法(CARS)实现对标准正态变换预处理后光谱数据的降维;研究基于全光谱以及特征光谱的预测苹果硬度BP网络模型。结果采用SPA和CARS分别从256个全光谱中提取了18个和16个特征波长,明显提升了预测模型的运行效率,且SPA+BP网络模型具有相对较好的苹果硬度预测能力(rp=0.728,RPm=0.282 kg/cm2)。结论研究表明基于高光谱成像技术和BP网络建立的预测模型可快速无损预测苹果的硬度。     

Magnetic particles as markers and carriers of biomolecules

The detection and manipulation of biomolecules on a common platform is of considerable interest not only for application in devices such as diagnostic tools but also for basic research in biological and medical systems. A promising approach is the utilisation of magnetic particles as markers and carriers for biomolecules. The principle functionality of this approach is demonstrated by the authors. Magnetic particles used as markers can be detected by highly sensitive magnetoresistive sensors resulting in a purely electronic signal. A direct comparison with the standard fluorescence method reveals the advantages of using the magnetic particles. In addition, magnetic particles used as carriers can be manipulated on-chip via currents running through especially designed line patterns. Some current drawbacks and future aspects are discussed. The combination of sensing and manipulating magnetic particles is a promising choice for future integrated lab-on-a-chip systems.     

A random-key encoded harmony search approach for energy-efficient production scheduling with shared resources

When seeking near-optimal solutions for complex scheduling problems, meta-heuristics demonstrate good performance with affordable computational effort. This has resulted in a gravitation towards these approaches when researching industrial use-cases such as energy-efficient production planning. However, much of the previous research makes assumptions about softer constraints that affect planning strategies and about how human planners interact with the algorithm in a live production environment. This article describes a job-shop problem that focuses on minimizing energy consumption across a production facility of shared resources. The application scenario is based on real facilities made available by the Irish Center for Manufacturing Research. The formulated problem is tackled via harmony search heuristics with random keys encoding. Simulation results are compared to a genetic algorithm, a simulated annealing approach and a first-come-first-served scheduling. The superior performance obtained by the proposed scheduler paves the way towards its practical implementation over industrial production chains.     

Modeling and estimation of signal-dependent noise in hyperspectral imagery

The majority of hyperspectral data exploitation algorithms are developed using statistical models for the data that include sensor noise. Hyperspectral data collected using charge-coupled devices or other photon detectors have sensor noise that is directly dependent on the amplitude of the signal collected. However, this signal dependence is often ignored. Additionally, the statistics of the noise can vary spatially and spectrally as a result of camera characteristics and the calibration process applied to the data. Here, we examine the expected noise characteristics of both raw and calibrated visible/near-infrared hyperspectral data and provide a method for estimating the noise statistics using calibration data or directly from the imagery if calibration data is unavailable.     

Terahertz encoding approach for secured chipless radio frequency identification

In this article, we present a new family of chipless tags, which permit encoding of digital data in the terahertz domain. These devices consist of stacked dielectric media whose thicknesses are of the same order as terahertz wavelengths. Since the information is encoded in the volume of these multilayer terahertz tags, they can easily be associated with classical identification techniques (e.g., barcode, radio frequency identification), where information is encoded at the surface of the tag, to provide higher data security. The principle of this encoding approach is studied and experimentally demonstrated in this paper. A 2 bit tag prototype has been realized and measured for validation purposes.     

Effect of the Magnetic Dipole–Dipole Interaction on the Capture Efficiency in Open Gradient Magnetic Separation

In magnetic separation, the magnetic dipole-dipole (DD) interaction between particles has an important effect on the capture efficiency. By producing transient particle agglomerations, this interaction can considerably speed up the separation process. To take into account adequately this effect in ferromagnetic particle random dispersion, we have developed a modeling approach. The approach is based on the coupling of the magnetic force equation and a local homogenizing model for the material magnetic permeability. To verify the efficiency of the proposed approach on one hand and to estimate the effect of the DD interaction on the particle capture on the other hand, we consider a problem of open gradient magnetic separation (OGMS). We also conducted a limited experimental verification of the transient agglomeration for fine ferromagnetic particles.     

Precision Synthesis: Designing Hot Spots over Hot Spots via Selective Gold Deposition on Silver Octahedra Edges

A major challenge in plasmonic hot spot fabrication is to efficiently increase the hot spot volumes on single metal nanoparticles to generate stronger signals in plasmon‐enhanced applications. Here, the synthesis of designer nanoparticles, where plasmonic‐active Au nanodots are selectively deposited onto the edge/tip hot spot regions of Ag nanoparticles, is demonstrated using a two‐step seed‐mediated precision synthesis approach. Such a “hot spots over hot spots” strategy leads to an efficient enhancement of the plasmonic hot spot volumes on single Ag nanoparticles. Through cathodoluminescence hyperspectral imaging of these selective edge gold‐deposited Ag octahedron (SEGSO), the increase in the areas and emission intensities of hot spots on Ag octahedra are directly visualized after Au deposition. Single‐particle surface‐enhanced Raman scattering (SERS) measurements demonstrate 10‐fold and 3‐fold larger SERS enhancement factors of the SEGSO as compared to pure Ag octahedra and non‐selective gold‐deposited Ag octahedra (NSEGSO), respectively. The experimental results corroborate well with theoretical simulations, where the local electromagnetic field enhancement of our SEGSO particles is 15‐fold and 1.3‐fold stronger than pure Ag octahedra and facet‐deposited particles, respectively. The growth mechanisms of such designer nanoparticles are also discussed together with a demonstration of the versatility of this synthetic protocol.