Single-element imaging spectrograph

A spectrograph concept designed for both high wavelength and high spatial resolution (in one dimension) is briefly described. This design is referred to as a single-element imaging spectrograph (SEIS). It is a one-bounce diffractive system that combines the spectral properties of a Rowland mount spectrograph with the imaging (spatial resolution) properties of a Wadsworth mount spectrograph through the use of a toroidal diffraction grating. No primary optics are necessary, making the system especially attractive for use in the extreme and far ultraviolet, where low reflectivity of common optical coatings can severely limit instrument sensitivity.     

Multi-wavelength raman imaging using a small-diameter image guide with a dimension-reduction imaging array

A commercially available fiber-optic Raman probe was modified for high-resolution spectral Raman imaging using a 350 microm diameter optical fiber image guide coupled to a dimension-reduction imaging array (DRIA). The DRIA comprised 672 optical fibers, arranged as a square array (21 x 32 fibers) on one end and a linear array (672 x 1 fibers) on the other. An imaging spectrograph was used with the DRIA to acquire multi-wavelength Raman images from -250 to 1800 cm(-1) at a spectral resolution of approximately 5 cm(-1). The utility of this technique for in situ and remote Raman imaging is demonstrated by monitoring the polymerization of a model polymer, dibromostyrene (DBS), while simultaneously measuring the Raman Stokes/ anti-Stokes ratio as a function of sample heating time, over a sample area of approximately 4 x 1.6 mm.     

Light profile microscopy based on Raman and wavelength resolved luminescence contrast

Light profile microscopy based on contrast from wavelength resolved Raman and luminescence measurements is demonstrated experimentally for the first time. A Raman/multispectral light profile microscope (RMSLPM) has been constructed based on a line profiling geometry in which the sample is irradiated with a tightly focused laser beam (of ten micrometers radius or less) behind a polished view surface and the resulting line image is dispersed over the wavelength using an imaging spectrograph. The instrumentation developed in this laboratory has a spectral resolution approaching 10 cm(-1) and an (actual) depth independent spatial resolution of 6-8 times the Rayleigh diffraction limit, limited at present by optical aberrations and alignment. The technique has the potential to image at approximately twice the Rayleigh diffraction limit. The spectral signatures reconstructed from a variety of common industrial polymers show excellent agreement with reference spectra from the literature, and may be used to identify individual layers in depth images of unknown materials. RMS-LPM image data based on luminescence contrast have also been used to provide concentration depth profiles of additives and degradation products in injection molded samples of high-density poly(ethylene) (HDPE).     

Raman Spectral Mapping of III–V Nitride and Graphene Nanostructures

Among several spectroscopic imaging techniques to visualise the nanostructures, Raman spectral imaging is one of the most indispensible non-destructive tools. We discuss the limitations and the importance of each step involved in the Raman imaging in the visualization of different nanostructures and illustrated with examples. Raman spectroscopic imaging of nanostructures is demonstrated for differentiation of morphology in InN nanorods, crystallographic orientation for single square faceted GaN nanotube and layer thickness of graphene layers. The limitations of the spatial and spectral resolutions of the Raman maps are evaluated in the illustration.     

A practical algorithm to remove cosmic spikes in Raman imaging data for pharmaceutical applications

Raman dispersive microscopic imaging techniques are finding ever-increasing applications in pharmaceutical research for their ability to provide spatial and spectral information about the sample. Spectral data acquired from dispersive Raman instruments utilizing charge-coupled device detectors are characterized by occasional high intensity spikes arising from cosmic ray events. These random cosmic spikes are superimposed on chemically meaningful spectra. Due to their high intensity and potential influence on variance structures, it is often crucial to filter cosmic spikes from data prior to the use of multivariate algorithms to extract chemical information from the image cube. Some extremely challenging cosmic spikes are found to seriously interfere with multivariate data analysis for our application, e.g., spikes with bandwidth greater than the bandwidth from species of interest, spikes in neighboring image pixels occurring at the same spectral channels, spikes right on top of the band of interest, etc. A practical algorithm is proposed for semiautomated cosmic spike removal. The algorithm is computationally efficient, conceptually simple, and easy to implement. It is an alternative to methods using repetitive measurements by taking advantage of the spatial characteristic of imaging techniques and existing knowledge from the formulation. The algorithm has been shown to generate recovered spectra with negligible spectral distortion. The utility of the algorithm will be illustrated by the analysis of Raman images of pharmaceutical samples.     

Quantitative imaging through a spectrograph. 2. Stoichiometry mapping by Raman scattering

The Bayesian deconvolution algorithm described in a preceding paper [Appl. Opt. 43, 5669-5681 (2004)] is applied to measurement of the two-dimensional stoichiometry field in a combustible methane-air mixture by Raman imaging through a spectrograph. Stoichiometry (fuel equivalence ratio) is derived from the number density fields of methane and nitrogen, with a signal-to-noise ratio of approximately 10 in a 600-laser-shot average. Prospects for single-shot Raman imaging are discussed.     

Raman microspectroscopy: a comparison of point, line, and wide-field imaging methodologies

Three different Raman microspectroscopic imaging methodologies using a single experimental configuration are compared; namely, point and line mapping, as representatives of serial imaging approaches, and direct or wide-field Raman imaging employing liquid-crystalline tunable filters are surveyed. Raman imaging data acquired with equivalent low-power 514.5-nm laser excitation and a cooled CCD camera are analyzed with respect to acquisition times, image quality, spatial resolution, intensity profiles along spatial coordinates, and spectral signal-to-noise ratios (SNRs). Point and line mapping techniques provide similar SNRs and reconstructed Raman images at spatial resolutions of approximately 1.1 microm. In contrast, higher spatial resolution is obtained by direct, global imaging (approximately 313 nm), allowing subtle morphological features on test samples to be resolved.     

Chemical imaging with a confocal scanning Fourier-transform-Raman microscope

Traditional approaches in confocal microscopy have focused on techniques to generate volumetric intensity or phase images of an object. In these different imaging modes the scattered optical-field properties depend on local refractive index and absorption, properties not unique to a given material. We report here on a confocal microscope that uses Raman scattered light to generate volumetric chemical images of a material. We designed and built a prototype instrument, called a confocal scanning laser Raman microscope, that combines a confocal scanning laser microscope with a Fourier-transform-Raman spectrometer. The high depth and lateral spatial resolution of the confocal optics design define a volume element from which the Raman scattered light is collected, and the spectrometer analyzes its spectral content. The sample is scanned through the microscope probe volume, and a chemical image isgenerated based on the content of the Raman spectrum extracted from each scan position in the sample. The results inclu e instrument characterization measurements and examples of confocal chemical imaging.     

Infrared microspectroscopy using prism-based spectrographs and focal plane array detection

Several prism-based spectrographs employing a mercury cadmium telluride (MCT) focal plane array detector have been interfaced to an infrared microscope. In the combined system, the area-defining aperture of the microscope also served as the entrance slit to the spectrograph. This investigation considered the fundamental limits of diffraction for both the spectrograph and microscope in order to determine both the spatial and spectral resolution of the system as a whole. Experimental results for spectral resolution, spectral range, and peak-to-peak noise have been presented. Finally, the dynamic capabilities of one spectrograph/microscope combination were investigated.     

Disentangling dynamic changes of multiple cellular components during the yeast cell cycle by in vivo multivariate Raman imaging

Cellular processes are intrinsically complex and dynamic, in which a myriad of cellular components including nucleic acids, proteins, membranes, and organelles are involved and undergo spatiotemporal changes. Label-free Raman imaging has proven powerful for studying such dynamic behaviors in vivo and at the molecular level. To construct Raman images, univariate data analysis has been commonly employed, but it cannot be free from uncertainties due to severely overlapped spectral information. Here, we demonstrate multivariate curve resolution analysis for time-lapse Raman imaging of a single dividing yeast cell. A four-dimensional (spectral variable, spatial positions in the two-dimensional image plane, and time sequence) Raman data "hypercube" is unfolded to a two-way array and then analyzed globally using multivariate curve resolution. The multivariate Raman imaging thus accomplished successfully disentangles dynamic changes of both concentrations and distributions of major cellular components (lipids, proteins, and polysaccharides) during the cell cycle of the yeast cell. The results show a drastic decrease in the amount of lipids by ~50% after cell division and uncover a protein-associated component that has not been detected with previous univariate approaches.     

Space-resolving flat-field extreme ultraviolet spectrograph system and its aberration analysis with wave-front aberration

The Nam aberration of a flat-field extreme ultraviolet spectrograph system, composed of a varied line-spacing concave grating and a toroidal mirror, was analyzed by calculating the wave-front aberration with respect to an astigmatic reference surface. The toroidal mirror was used to compensate for the astigmatism that was due to the grazing incidence of light at the concave grating. The spectrograph system could form a space-resolved spectrum along the sagittal direction. The spectral and spatial resolutions of the spectrograph system were estimated from the root-mean-square spot size. The actual spectral resolution of the spectrograph system was measured from extreme ultraviolet spectra obtained from plasmas produced by an iodine laser having an energy of 0.5 J in a 4-ns duration, and it was compared with the calculated value.     

Characterization of chloramphenicol palmitate drug polymorphs by Raman mapping with multivariate image segmentation using a spatial directed agglomeration clustering method

Chemical imaging analysis holds great potential in probing the chemical heterogeneity of samples with high spatial resolution and molecular specificity. This paper demonstrates the implementation of Raman mapping for microscopic characterization of tablets containing chloramphenicol palmitate polymorphs with the aid of a new multivariate image segmentation approach based on spatial directed agglomeration clustering. This approach performs the agglomeration clustering by stepwise merging the pixels possessing both spatial closeness and spectral similarity into clusters that define the image segmentation. The incorporation of spatial closeness into the clustering process enables the approach to improve the robustness and avoid poorly defined image segmentation arising from clusters with highly separated pixels. Additionally, the stepwise merging of clusters offers an F-statistic-based procedure to automatically ascertain the number of image segments. Raman mapping analysis of tablets containing two polymorphs of chloramphenicol palmitate followed by multivariate image segmentation reveals that the proposed technique offers the identification of each polymorph and a quantitative visualization of the spatial distribution of the polymorphs identified. This technique holds promise in rapid, noninvasive, and quantitative polymorph analysis for pharmaceutical production processes.     

Hybrid confocal Raman fluorescence microscopy on single cells using semiconductor quantum dots

We have overcome the traditional incompatibility of Raman microscopy with fluorescence microscopy by exploiting the optical properties of semiconductor fluorescent quantum dots (QDs). Here we present a hybrid Raman fluorescence spectral imaging approach for single-cell microscopy applications. We show that resonant Raman imaging of flavocytochrome b558 at 413.1 nm excitation in QD-labeled neutrophilic granulocytes or nonresonant Raman imaging of proteins and lipids at 647.1 nm excitation in QD-labeled macrophages can be integrated with linear one-photon excitation and nonlinear continuous-wave two-photon excitation fluorescence microscopy of QDs, respectively. The enhanced information content of these two hybrid Raman fluorescence methods provides new multiplexing possibilities for single-cell optical microscopy and intracellular chemical analysis.     

Ultraviolet-visible spectrograph optics: ODIN project

We describe one of the possible designs for the UV-visible spectrograph optics to be employed in the ODIN project. The spectrograph will be used in a future satellite mission for aeronomy observations and will image a column of atmosphere just above the Earth's surface onto a two-dimensional CCD array with the spatial and spectral content aligned orthogonal to one another.     

Fuzzy clustering of Raman spectral imaging data with a wavelet-based noise-reduction approach

Raman spectral imaging has been widely used for extracting chemical information from biological specimens. One of the challenges is to cluster the chemical groups from the vast amount of hyperdimensional spectral imaging data so that functionally similar groups can be identified. In this paper, we present an approach that combines a differential wavelet-based data smoothing with a fuzzy clustering algorithm for the classification of Raman spectral images. The preprocessing of the spectral data is facilitated by decomposing them in the differential wavelet domain, where the discrimination of true spectral features and noise can be easily performed using a multi-scale pointwise product (MPP) criterion. This approach is applied to the classification of spectral data collected from adhesive/dentin interface specimens where the spectral data exhibit different signal-to-noise ratios. The proposed wavelet approach has been compared to several conventional noise-removal algorithms.     

Stray light correction algorithm for multichannel hyperspectral spectrographs

An algorithm is presented that corrects a multichannel fiber-coupled spectrograph for stray or scattered light within the system. The efficacy of the algorithm is evaluated based on a series of validation measurements of sources with different spectral distributions. This is the first application of a scattered-light correction algorithm to a multichannel hyperspectral spectrograph. The algorithm, based on characterization measurements using a tunable laser system, can be extended to correct for finite point-spread response in imaging systems.     

Two-dimensional mapping of the electron density in laser-produced plasmas

We performed two-dimensional (2D) mapping of the electron density in a laser-produced plasma with high spatial and temporal resolution. The plasma was produced by irradiating an aluminum target with 1064 nm, 6 ns pulses from a Nd:YAG laser under vacuum conditions. Stark broadening of the lines was used to estimate the electron density at various locations inside the plasma. The 2D spectral images were captured at different spatial points in the plasma using an imaging spectrograph coupled to an intensified CCD at various times during the plasma expansion. A comparison between radially averaged and radially resolved electron density profiles showed differences in the estimated values at the earlier times of plume evolution and closer distances to the target. However, the measured radially averaged values are consistent with 2D radial profiles at later times and/or farther distances from the target surface.     

Proposal for aberration-corrected imaging spectrograph

We propose a novel flat-field imaging spectrograph that consists of two plane gratings, four spherical mirrors, and two plane mirrors. The imaging spectrograph is designed in such a manner that the primary and the secondary principal points of the whole optical system for the horizontal direction coincide with those for the vertical direction. In a paraxial approximation, it is essentially aberration free because an entrance slit and an imaging detector are placed on the primary and the secondary principal planes, respectively. Spot diagrams obtained from ray-tracing procedures have indicated that the proposed spectrograph is superior to the conventional Czerny-Turner mounting.     

Analysis of hyperspectral fluorescence images for poultry skin tumor inspection

We present a hyperspectral fluorescence imaging system with a fuzzy inference scheme for detecting skin tumors on poultry carcasses. Hyperspectral images reveal spatial and spectral information useful for finding pathological lesions or contaminants on agricultural products. Skin tumors are not obvious because the visual signature appears as a shape distortion rather than a discoloration. Fluorescence imaging allows the visualization of poultry skin tumors more easily than reflectance. The hyperspectral image samples obtained for this poultry tumor inspection contain 65 spectral bands of fluorescence in the visible region of the spectrum at wavelengths ranging from 425 to 711 nm. The large amount of hyperspectral image data is compressed by use of a discrete wavelet transform in the spatial domain. Principal-component analysis provides an effective compressed representation of the spectral signal of each pixel in the spectral domain. A small number of significant features are extracted from two major spectral peaks of relative fluorescence intensity that have been identified as meaningful spectral bands for detecting tumors. A fuzzy inference scheme that uses a small number of fuzzy rules and Gaussian membership functions successfully detects skin tumors on poultry carcasses. Spatial-filtering techniques are used to significantly reduce false positives.     

高速窄带多光谱成像系统光谱重建技术研究

光谱成像技术可以同时从光谱维和空间维上获取被测目标的信息，即结合了空间成像系统和光谱检测系统的功能，因此近年在影像获取与处理领域中倍受重视。本论文基于窄带多光谱成像技术建立八通道CCD多光谱成像系统，它能够实时采集八个通道的图像，获得波长分布从可见到红外（420-940nm）八个波段的光谱响应值。在此基础上对图像进行位置配准、反射率定标、采用插值算法获得其它波段光谱响应值，最终能够获取图像中任意一点的光谱反射率及颜色参数。实验结果表明，本文使用的三次样条插值法对原始光谱图像进行平滑操作的方法是有效的，能够以一定精度模拟出目标物点的真实光谱特性。该系统在动态目标检测识别、艺术品评价复制等领域有着广阔的应用前景。