Image Cube Research Articles

Compositional diversity of near-, far-side transitory zone around Naonobu, Webb and Sinus Successus craters: Inferences from Chandrayaan-1 Moon Mineralogy Mapper (M3) data

This study investigated the potential of Moon Mineralogy Mapper (M3) data for studying compositional variation in the near-, far-side transition zone of the lunar surface. For this purpose, the radiance values of the M3 data were corrected for illumination and emission related effects and converted to apparent reflectance. Dimensionality of the calibrated reflectance image cube was reduced using Independent Component Analysis (ICA) and endmembers were extracted by using Pixel Purity Index (PPI) algorithm. The selected endmembers were linearly unmixed and resolved for mineralogy using United States Geological Survey (USGS) library spectra of minerals. These mineralogically resolved endmembers were used to map the compositional variability within, and outside craters using Spectral Angle Mapper (SAM) algorithm. Cross validation for certain litho types was attempted using band ratios like Optical Maturity (OMAT), Color Ratio Composite and Integrated Band Depth ratio (IBD). The identified lithologies for highland and basin areas match well with published works and strongly support depth related magmatic differentiation. Prevalence of pigeonite-basalt, pigeonite-norite and pyroxenite in crater peaks and floors are unique to the investigated area and are attributed to local, lateral compositional variability in magma composition due to pressure, temperature, and rate of cooling.

WIDE INTEGRAL-FIELD INFRARED SPECTROSCOPY OF THE BRIGHT [Fe II] SHELL IN THE YOUNG SUPERNOVA REMNANT G11.2–0.3

We present the results of wide integral-field near-infrared (1.0-1.8 um) spectroscopic observations of the southeastern shell of the young core-collapse supernova remnant (SNR) G11.2-0.3. We first construct [Fe II] 1.644 um line images of three bright clumps from the obtained spectral image cubes and compare them with those of other transitions such as [Fe II] 1.257, [Fe II] 1.534 and He I 1.083 um line images. This allows us to estimate the electron density (~ 4,700-9,400 cm^-3) and extinction (Av ~ 16-20 mag) of the shell, including detailed two-dimensional distribution of the properties in the brightest clump, as well as the discovery of a faint high-velocity (~ -440 km/s) component in the clump. Our SNR shock model calculations estimate the preshock number density of ~ 250-500 cm^-3 and shock speed of ~ 80-250 km/s in the [Fe II]-emitting region of the SNR. The comparison between the observed and modelled radial profiles of the line intensities and their ratios reveals that the shell is composed of multiple thin filaments which have been likely formed in episodic mass loss processes of a progenitor star. The discovery of the faint high-velocity component supports the interpretation that the southeastern shell of G11.2-0.3 is mainly composed of circumstellar material with contamination by supernova ejecta and also that its ejected material was expelled primarily in the southeast-northwest direction.

Feature Extraction of Hyperspectral Image Cubes Using Three-Dimensional Gray-Level Cooccurrence

This paper presents a novel approach for the feature extraction of hyperspectral image cubes. In this paper, hyperspectral image cubes are treated as volumetric data sets. Features that are most helpful in separating different targets are effectively extracted from the hyperspectral image cubes using a newly developed high-order texture analysis method. The traditional texture measure of the gray-level cooccurrence matrix is extended to a 3-D tensor field to explore the complicated volumetric data more effectively and to extract discriminant features for better classification. As the kernel size is one of the most important parameters in statistics-based texture analysis, a semivariance analysis and a spectral separability measure are used to determine the most appropriate kernel size in the spatial and spectral domains, respectively, for computing 3-D gray-level cooccurrence. In addition, a few statistical indexes are also extended to third-order forms in order to calculate quantitative texture properties of the generated cooccurrence tensor field. An airborne hyperspectral data set and an EO-1 Hyperion image are used to test the performance of the developed algorithms. Experimental results indicate that the developed 3-D texture analysis outperforms conventional second-order texture descriptors and the support vector machine-based classifier in supervised classifications of both hyperspectral data sets.

Multi-temporal hyperspectral mixture analysis and feature selection for invasive species mapping in rainforests

We evaluated the potential of a multi-temporal Multiple Endmember Spectral Mixture Analysis (MESMA) for invasive species mapping in Hawaiian rainforests. Earth Observing-1 Hyperion time series data were compiled in a single image cube and ingested into MESMA. While the temporal analysis provided a way to incorporate species phenology, a feature selection technique automatically identified the best time and best spectral feature set to optimize the separability among the native and invasive tree species in our study area. We initiated an alternative Separability Index (SI)-based feature selection approach in which a boundary condition reduced the amount of correlation in the selected spectral subset. We hypothesized that redundant spectral information could be avoided, and improved plant detection accuracy could be achieved, with reduced computational time due to the selection of fewer bands in the mixture analysis. Our analysis showed a systematic increase in the invasive species detection success when we compared the output of multi-temporal MESMA (Kappa=0.78) with that of the traditional unitemporal approach (Kappa=0.51–0.69). Even for unitemporal MESMA, in which only a single input image was used, the band selection strategy was beneficial both in plant detection accuracy and computational time. We could further demonstrate that, despite a lack of imagery covering all phenological events, a proper band selection strategy can emphasize subtle spectral and phenological differences between species and can thereby partly compensate for this lack of data. This creates opportunities for mapping in areas where cloud cover is a limiting factor for building extended spectral image time series. This approach is sufficiently general and inherently adaptive, thereby supporting species mapping using Hyperion and forthcoming space-borne imaging spectrometers.

Image Registration with Hyperspectral Data Based on Fourier-Mellin Transform

Hyperspectral imagery is playing more and more important role in many fields such as geology, agriculture, environment, military, atmosphere and so on. We need to register Hyperspectral imagery so that we can build coherent image cubes and get coherent spectrum of pixels. Our concern in this paper is the Fourier-Mellin Transform (FMT) for image registration process and its related techniques for real hyperspectral data. FMT can recover translation, rotation. It is computationally efficient. Techniques such as filter, window and downscale for improving precision in the registration process are taken/put forward and discussed. With highpass emphasis filter and downscale for registration of real hyperspectral data can get a right or better result in some situation.

High spatial and temporal resolution sampling of Martian gas abundances from CRISM spectra

The Compact Reconnaissance Imaging Spectrometer for Mars on the Mars Reconnaissance Orbiter spacecraft has been collecting spectra in the visible to near‐infrared wavelength range for over 5 years (approximately 3 Martian years). Observations consist of image cubes, with two main selections of spectral sampling (74 and 545 spectral channels) and two main selections of spatial sampling (approximately 20 and 200 m/pixel). Retrievals of gas abundances, specifically CO2, H2O, and CO, are performed from spectra collected in all observation modes. The retrievals are efficiently performed using a look‐up table, where the strength of gas absorption features are precalculated for an N‐dimensional discrete grid of known input parameters (season, location, environment, viewing geometry, etc.) and the one unknown parameter to be retrieved (gas abundance). A reverse interpolation in the look‐up table is used to match the observed strength of the gas absorption to the gas abundance. This algorithm is extremely fast compared to traditional radiative transfer computations that seek to recursively fit calculated results to an observed spectral feature, and can therefore be applied on a pixel‐by‐pixel basis to the tens of thousands of Compact Reconnaissance Imaging Spectrometer for Mars images, to examine cross‐scene structure as well as to produce climatological averages.

Endoskopie des Larynx mit Hyperspectral Imaging

Hyperspectral imaging has been proven to be useful in remote earth sensing, e.g., satellite-based classification of vegetation. After modifying it for in vivo evaluation of the larynx using microscopy, we show its adoption for endoscopes. In addition to routine microlaryngoscopies under white light inspection, the laryngoscopy was also performed with not only a conventional operation microscope mounted with a tuneable monochromatic light source and a synchronously triggered monochromatic CCD camera (n = 47 patients), but also a similarly modified rigid 0° endoscope (n = 16 patients). Hyperspectral image cubes were obtained between 390 and 680 nm, analyzed using established software tools, and the data using microscope versus endoscope were compared. Under endoscopy, illumination was more even and sterical resolution appeared unchanged at significantly shorter image acquisition times. Hyperspectral classification delineated areas of altered mucosa without further external information irrespective of whether image cubes were generated with microscopy or endoscopy. Hyperspectral imaging can be transferred not only to micro(laryngo)scopy but also to endoscopy with rigid optics. This opens the way to a variety of clinically relevant anatomical regions (e.g., upper aerodigestive tract). Its adoption to flexible optics will further broaden this spectrum.

Classification of visible point sources using hyperspectral chromotomosynthetic imagery

A hyperspectral chromotomosynthetic imaging (CTI) system is used to detect and classify a collection of 21 scattered, spectrally diverse point-like sources. The instrument operates in the visible to near IR (400 to 800 nm) and has the potential to collect spectral imagery at great than 10 Hz. A two-dimensional wideband spatial image of the target scene is used to detect and spatially characterize the targets leading to optimization of the three-dimensional (3-D) spatial/spectral reconstruction of the hyperspectral image cube. The instrument is assessed by directly comparing results to spatial data collected by a wideband image and hyperspectral data collected using a liquid crystal tunable filter (LCTF). Target classification using k-means clustering of observed spectra yielded 5 to 6 target classes for each methodology, indicating information obtained using CTI was similar to that collected by the LCTF. The wide-band spatial content of the scene reconstructed from the CTI data is of same or better quality in terms of background noise and target intensities as a single frame collected by the undispersed imaging system with projections taken at every 1 deg. Performance is dependent on the number of projections used, with projections at 5 deg producing adequate results in terms of target characterization. The CTI has 2 to 4 times the spectral resolution of the LCTF. The data collected by the CTI system can simultaneously provide spatial information of equal quality as a the bandpass imaging system, provide high-frame rate slitless one-dimensional spectra, and generate 3-D hyperspectral imagery which can be exploited to provide the same results as a traditional multiband spectral imaging system.

Migration velocity analysis using traveltime wavefield tomography

We introduce an integrated wave-equation technique for migration velocity analysis (MVA) that consists of three steps: (1) forming the extended data, (2) approximating the correct transmitted wavefield, and (3) using wavefield tomography to update the velocity model. In the first step, the crosscorrelation imaging condition is relaxed to produce other nonzero-lag common image gathers (CIG) that, combined, form a common image cube (CIC). Slicing the CIC at different crosscorrelation lags forms a series of CIGs. Flattened events will occur in the CIGs at a lag other than the zero-lag when an incorrect velocity model is used in the migration. In the second step, for each event on the CIG, we pick the focusing depth and crosscorrelation lag at which it is flattest. We then model a Green’s function by seeding a source at the focusing depth using one-way wave equation modeling, then shift the modeled wavefield with the focusing crosscorrelation lag. This process is repeated for the other primary events at different lateral and vertical positions. The result is a set of modeled data whose wavefield approximates the wavefield that would have been generated if the correct velocity model had been used to simulate these gathers. We then apply wavefield tomography on these data-driven modeled data to update the velocity model. Our inversion scheme is based on wave-equation traveltime tomography that can update the velocity model in the presence of large velocity errors and a complex environment. Tests on synthetic and real 2D seismic data confirm the method’s effectiveness in building velocity models in complex structural areas that have large lateral velocity variations.

Instrumental error in chromotomosynthetic hyperspectral imaging

Chromotomosynthetic imaging (CTI) is a method of convolving spatial and spectral information that can be reconstructed into a hyperspectral image cube using the same transforms employed in medical tomosynthesis. A direct vision prism instrument operating in the visible (400-725 nm) with 0.6 mrad instantaneous field of view (IFOV) and 0.6-10 nm spectral resolution has been constructed and characterized. Reconstruction of hyperspectral data cubes requires an estimation of the instrument component properties that define the forward transform. We analyze the systematic instrumental error in collected projection data resulting from prism spectral dispersion, prism alignment, detector array position, and prism rotation angle. The shifting and broadening of both the spectral lineshape function and the spatial point spread function in the reconstructed hyperspectral imagery is compared with experimental results for monochromatic point sources. The shorter wavelength (λ<500 nm) region where the prism has the highest spectral dispersion suffers mostly from degradation of spectral resolution in the presence of systematic error, while longer wavelengths (λ>600 nm) suffer mostly from a shift of the spectral peaks. The quality of the reconstructed hyperspectral imagery is most sensitive to the misalignment of the prism rotation mount. With less than 1° total angular error in the two axes of freedom, spectral resolution was degraded by as much as a factor of 2 in the blue spectral region. For larger errors than this, spectral peaks begin to split into bimodal distributions, and spatial point response functions are reconstructed in rings with radii proportional to wavelength and spatial resolution.

MULTIMOMENT RADIO TRANSIENT DETECTION

We present a multimoment technique for signal classification and apply it to the detection of fast radio transients in incoherently dedispersed data. Specifically, we define a spectral modulation index in terms of the fractional variation in intensity across a spectrum. A signal whose intensity is distributed evenly across the entire band has a much lower modulation index than a spectrum with the same intensity localized in a single channel. We are interested in broadband pulses and use the modulation index to excise narrowband radio frequency interference (RFI) by applying a modulation index threshold above which candidate events are removed. The technique is tested both with simulations and using data from sources of known radio pulses (RRAT J1928+15 and giant pulses from the Crab pulsar). We find that our technique is effective at eliminating not only narrowband RFI but also spurious signals from bright, real pulses that are dedispersed at incorrect dispersion measures. The method is generalized to coherent dedispersion, image cubes, and astrophysical narrowband signals that are steady in time. We suggest that the modulation index, along with other statistics using higher-order moments, should be incorporated into signal detection pipelines to characterize and classify signals.

New Approach in Image Compression: 3D Spiral JPEG

This paper presents a new JPEG-based lossy image compression method based on three-dimensional formation of the original image by spiral order scanning and 3D discrete cosine transformation (DCT). The proposed spiral scanning results in similar information blocks to be in the same 8x8x8 cube. The proposed quantization table and method for converting a 3D image cube into a ID array provide better coding efficiency in run length coding. Hence, a better performance in a wide range of images is obtained. The performance of the proposed compression method is measured over various images, and it is observed that the proposed method has better performance than that of conventional JPEG compression especially in low and in high bit rates. In addition, the proposed compression scheme has generally superior performance in images where there is substantial amount of background.

Code aperture optimization for spectrally agile compressive imaging

Coded aperture snapshot spectral imaging (CASSI) provides a mechanism for capturing a 3D spectral cube with a single shot 2D measurement. In many applications selective spectral imaging is sought since relevant information often lies within a subset of spectral bands. Capturing and reconstructing all the spectral bands in the observed image cube, to then throw away a large portion of this data, is inefficient. To this end, this paper extends the concept of CASSI to a system admitting multiple shot measurements, which leads not only to higher quality of reconstruction but also to spectrally selective imaging when the sequence of code aperture patterns is optimized. The aperture code optimization problem is shown to be analogous to the optimization of a constrained multichannel filter bank. The optimal code apertures allow the decomposition of the CASSI measurement into several subsets, each having information from only a few selected spectral bands. The rich theory of compressive sensing is used to effectively reconstruct the spectral bands of interest from the measurements. A number of simulations are developed to illustrate the spectral imaging characteristics attained by optimal aperture codes.

Potential of a custom-designed fluorescence imager combined with multivariate statistics for the study of chemical and mechanical characteristics of beef meat

The potential of fluorescence imaging to discriminate different bovine muscles in relation with animal age, muscle type, chemical and mechanical properties was examined. Twenty-four muscles of three types ( Gluteus medius, Longissimus dorsi, and Semitendinosus) and two animal age groups (10–13-years old and 12–24-months old) were obtained from the carcasses of Limousin breed cows. One hundred and forty-four images were collected at three illuminating conditions (exc 320 nm, exc 380 nm, and white light) using a custom-designed imager. The image cubes were processed using “regionprops” algorithm developed earlier in order to extract image shape features ( number of shapes, area, major- axis- length, eccentricity, and solidity). Extracted image shape features were processed using custom-designed programs. The results of the PLSDA performed on image shape features showed 100% good discrimination for the three types of muscles. Muscle samples were also subjected to chemical analysis (dry matter, fat, pyridinoline, total, insoluble and soluble collagen) and mechanical tests (shear stress and breaking energy). PLSR models indicated relations between extracted image shape features and mechanical properties, i.e., R 2 = 0.69 and RMSEV = 0.514 were observed for breaking energy for adult-animal muscles. Regarding chemical composition, image shape features allowed to predict total collagen of L. dorsi with R 2 = 0.61 and RMSEV = 0.756. This study has demonstrated a promising potential of the custom-designed fluorescence imager combined with multivariate statistical tools in the study of beef meat.

THE ARIZONA RADIO OBSERVATORY CO MAPPING SURVEY OF GALACTIC MOLECULAR CLOUDS. II. THE W3 REGION IN CO J = 2-1, 13 CO J = 2-1, AND CO J = 3-2 EMISSION

We present fully sampled 38'' resolution maps of the CO and 13CO J = 2-1 lines in the molecular clouds toward the H II region complex W3. The maps cover a 20 × 167 section of the galactic plane and span –70 to –20 km s–1 (LSR) in velocity with a resolution of ~1.3 km s–1. The velocity range of the images includes all the gas in the Perseus spiral arm. We also present maps of CO J = 3-2 emission for a 05 × 033 area containing the H II regions W3 Main and W3(OH). The J = 3-2 maps have velocity resolution of 0.87 km s–1 and 24'' angular resolution. Color figures display the peak line brightness temperature, the velocity-integrated intensity, and velocity channel maps for all three lines, and also the (CO/13CO) J = 2-1 line intensity ratios as a function of velocity. The line intensity image cubes are made available in standard FITS format as electronically readable files. We compare our molecular line maps with the 1.1 mm continuum image from the BOLOCAM Galactic Plane Survey (BGPS). From our 13CO image cube, we derive kinematic information for the 65 BGPS sources in the mapped field, in the form of Gaussian component fits.

Migration velocity analysis using the common image cube (CIC)

Migration velocity analysis (MVA) is commonly performed in the image domain in conjunction with ray-based tomography to update the velocity model. This approach can be challenging in the presence of large velocity errors as it may require many MVA iterations before converging to a model that can focus the events in the image domain. We introduced a downward continuation-based domain for carrying out MVA that is more flexible than conventional domains. This approach consists of two steps: (1) forming the common image cube (CIC) and (2) modeling the Green’s functions. In the first step, the cross-correlation imaging condition is relaxed to produce more than the zero lag common image gather (CIG). Slicing these data at different lags forms a series of CIGs, whereas a conventional CIG can be obtained by slicing the cube at the zero lag. When the velocity model used for the migration differs from the true velocity model, properly flattened events may occur in CIGs other than the zero lag. In the second step, for each event on the CIG, we picked the cross-correlation lag and depth at which it flattens best. For each event, we modeled a Green’s function by seeding a source at the focusing depth using one-way wave-equation modeling. This process is then repeated for other events at different lateral positions. The result is a set of Green’s functions whose wavefield approximates the ones that would have been generated if the correct velocity model was used to simulate these gathers. The updated Green functions are easier to work with than the raw data as they have less noise. Wavefield tomography can then be applied on these data-driven, modeled Green’s functions to build the final velocity model. Tests on synthetic and real 2D data confirm the method’s effectiveness in building velocity models in complex structural areas with large lateral velocity variations.

Jovian chromophore characteristics from multispectral HST images

The chromophores responsible for coloring the jovian atmosphere are embedded within Jupiter’s vertical aerosol structure. Sunlight propagates through this vertical distribution of aerosol particles, whose colors are defined by ϖ 0( λ), and we remotely observe the culmination of the radiative transfer as I/ F( λ). In this study, we employed a radiative transfer code to retrieve ϖ 0( λ) for particles in Jupiter’s tropospheric haze at seven wavelengths in the near-UV and visible regimes. The data consisted of images of the 2008 passage of Oval BA to the south of the Great Red Spot obtained by the Wide Field Planetary Camera 2 on-board the Hubble Space Telescope. We present derived particle colors for locations that were selected from 14 weather regions, which spanned a large range of observed colors. All ϖ 0( λ) curves were absorbing in the blue, and ϖ 0( λ) increased monotonically to approximately unity as wavelength increased. We found accurate fits to all ϖ 0( λ) curves using an empirically derived functional form: ϖ 0( λ) = 1 − A exp(− Bλ). The best-fit parameters for the mean ϖ 0( λ) curve were A = 25.4 and B = 0.0149 for λ in units of nm. We performed a principal component analysis (PCA) on our ϖ 0( λ) results and found that one or two independent chromophores were sufficient to produce the variations in ϖ 0( λ). A PCA of I/ F( λ) for the same jovian locations resulted in principal components (PCs) with roughly the same variances as the ϖ 0( λ) PCA, but they did not result in a one-to-one mapping of PC amplitudes between the ϖ 0( λ) PCA and I/ F( λ) PCA. We suggest that statistical analyses performed on I/ F( λ) image cubes have limited applicability to the characterization of chromophores in the jovian atmosphere due to the sensitivity of I/ F( λ) to horizontal variations in the vertical aerosol distribution.

Anomaly detection with varied ground sample distance utilizing spectropolarimetric imagery collected using a liquid crystal tunable filter

Liquid crystal tunable filters (LCTFs) are a technology that can act as both a spectral and linear polarization filter for an imaging device. Paired with the appropriate hardware, a LCTF can be configured to collect hyperspectral Stokes imagery which contains both spectral as well as polarimetric information on a per-pixel level basis. This data is used to investigate the utility of spectro-polarimetric data with standard spectral analysis algorithms, in this case anomaly detection. A method to simulate different ground sample distances (GSDs) is used to illustrate the effect on algorithm performance. In this paper, a spectro-polarimetric imager is presented that can collect spectro-polarimetric image cubes in units of calibrated sensor reaching radiance. The system is used to collect imagery of two scenes, each containing die-cast scale vehicles and different background types. An anomaly detector is applied to the intensity and polarized image cubes to find those pixels that are different from the background spectrally and/or polarimetrically. The effect of changing the apparent GSD on the anomaly detection performance is explored. This shows that applying anomaly detection to spectro-polarimetric data can improve the false alarm rate over standard spectral data for finding certain types of man-made objects in complex backgrounds.

Near-Infrared Luminescence of Cadmium Pigments: In Situ Identification and Mapping in Paintings

A comprehensive study of the luminescence properties of cadmium pigments was undertaken to determine whether these properties could be used for in situ identification and mapping of the pigments in paintings. Cadmium pigments are semiconductors that show band edge luminescence in the visible range and deep trap luminescence in the red/infrared range. Emission maxima, quantum yields, and excitation spectra from the band edge and deep trap emissions were studied for sixty commercial cadmium pigments that span the color range from yellow to red (reflectance transition 470 to 660 nm). For paints containing cadmium pigments, luminescence from deep traps was more readily observable than that from the band edge, although the yield varied widely from zero to around 4.5%. Optimal excitation for emission is found to be in the visible for both pigments in powder form and mixed with a medium. The maxima of the deep trap emission shift with the band gap energy, providing a potentially useful way to assign pigment type even when used in pigment mixtures. The usefulness of the results of the study on mockups was demonstrated by the mapping of cadmium pigments of different hues with the aid of calibrated luminescence imaging spectroscopy in a painting by Edward Steichen, entitled Study for 'Le Tournesol' (1920). Analysis of the luminescence image cube reveals at least six unique spectral components, associated with emission from white pigments, paint binder, and cadmium red and yellow pigments. The results were compared with those from X-ray fluorescence spectrometry (XRF) and fiber-optic reflection spectroscopy (FORS) and the results obtained on paint samples containing cadmium pigments. These results show that, when present, the emission from traps can be used as an analytical tool to identify cadmium pigments, to distinguish among cadmium sulfide, cadmium zinc sulfide, and cadmium sulfoselenide, and to map cadmium pigments, even in mixtures.

Advanced Spectral Imaging for Noninvasive Microanalysis of Cultural Heritage Materials: Review of Application to Documents in the U.S. Library of Congress

Hyperspectral imaging was originally developed for remote sensing and astronomical applications, but adaptations of this technology have been of great benefit to the preservation of cultural heritage. Developments in noninvasive analytical techniques have advanced the preservation of cultural heritage materials by enabling the identification and analysis of a range of materials, utilizing their unique spectral response to nondestructively determine chemical composition, and determining states of deterioration and change due to environmental conditions. When used as a tool for noninvasive characterization of cultural heritage, these spectral imaging systems allow the collection of chemical identification information about materials without sampling, which is a critical factor for cultural heritage materials. The United States Library of Congress has been developing the application of hyperspectral imaging to the preservation and analysis of cultural heritage materials as a powerful noncontact technique. It allows noninvasive characterization of materials, by identifying and characterizing colorants, inks, and substrates with narrow-band illumination to protect the object while also monitoring deterioration or changes due to exhibit and other environmental conditions. Contiguous illumination from the ultraviolet, visible, and infrared spectral regions allows the capture of lost, obscured, and deteriorated information. The resulting image cube allows greater capabilities for mapping and coordinating a range of complementary chemical and spectral analyses. The capabilities of this technique are illustrated by a review of results from analysis of the Waldseemüller World Map, the L'Enfant plan for Washington, D.C., and the first draft of the U.S. Declaration of Independence.