Multispectral optical imaging combinedin situwith XPS or ToFSIMS and principal component analysis (original) (raw)
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In recent times, multispectral imaging techniques have increasingly become a part of the range of examination and analytical methodologies that conservation professionals have at their disposal for the investigation of cultural heritage objects. These techniques, which include both luminescence (emitted light) imaging methods (ultraviolet-induced luminescence (UVL); visible-induced infrared luminescence (VIL) and visible-induced visible luminescence (VIVL)) and a range of related broadband reflectance imaging methods (visible reflectance (VIS), infrared reflectance (IRR) and ultraviolet reflectance (UVR)), are not only used by scientists but are also increasingly being adopted by a much wider range of users including conservators, archaeologists and curators, in more diverse and challenging settings. However, although attractive in offering qualitative, non-invasive and often relatively inexpensive and portable tools for spatial localisation of specific materials or material types, the equipment, capture and processing of imagesparticularly those used in luminescence imaginghave tended to be highly dependent on individual users and the set-up they employ, making cross-comparison between different institutions and researchers very difficult. It has thus become evident that there is a need to establish a clear set of widelyaccessible methods and protocols from which to work.
CHARISMA, 2013
In recent times, multispectral imaging techniques have increasingly become a part of the range of examination and analytical methodologies that conservation professionals have at their disposal for the investigation of cultural heritage objects. These techniques, which include both luminescence (emitted light) imaging methods (ultraviolet-induced luminescence (UVL); visible-induced infrared luminescence (VIL) and visible-induced visible luminescence (VIVL)) and a range of related broadband reflectance imaging methods (visible reflectance (VIS), infrared reflectance (IRR) and ultraviolet reflectance (UVR)), are not only used by scientists but are also increasingly being adopted by a much wider range of users including conservators, archaeologists and curators, in more diverse and challenging settings. However, although attractive in offering qualitative, non-invasive and often relatively inexpensive and portable tools for spatial localisation of specific materials or material types, the equipment, capture and processing of imagesparticularly those used in luminescence imaginghave tended to be highly dependent on individual users and the set-up they employ, making cross-comparison between different institutions and researchers very difficult. It has thus become evident that there is a need to establish a clear set of widelyaccessible methods and protocols from which to work.
Multivariate analysis of extremely large ToFSIMS imaging datasets by a rapid PCA method
Surface and Interface Analysis, 2015
Principal component analysis (PCA) and other multivariate analysis methods have been used increasingly to analyse and understand depth profiles in X-ray photoelectron spectroscopy (XPS), Auger electron spectroscopy (AES) and secondary ion mass spectrometry (SIMS). These methods have proved equally useful in fundamental studies as in applied work where speed of interpretation is very valuable. Until now these methods have been difficult to apply to very large datasets such as spectra associated with 2D images or 3D depth-profiles. Existing algorithms for computing PCA matrices have been either too slow or demanded more memory than is available on desktop PCs. This often forces analysts to 'bin' spectra on much more coarse a grid than they would like, perhaps even to unity mass bins even though much higher resolution is available, or select only part of an image for PCA analysis, even though PCA of the full data would be preferred.
Development and analytical applications of multispectral imaging techniques: an overview
Fresenius' journal of analytical chemistry, 2001
A multispectral imaging spectrometer is an instrument that can simultaneously record spectral and spatial information of a sample. Chemical and physical properties of the sample can be elucidated from such images. By synergistic use of an acousto-optic tunable filter and a progressive scan camera capable of snap shot recording it was possible to develop a novel imaging spectrometer with a spatial resolution of a few microns and which can record, grab and store up to 33 images per second (at a function of time) or 16 images per second (as a function of wavelength). This overview article summarizes the instrumentation development of various imaging spectrometers and their applications including its use as the detector for the determination of identity and sequences of peptides synthesized by the combinatorial solid phase method.
Multivariate image analysis methods applied to XPS imaging data sets
Recent improvements in imaging photoelectron spectroscopy enhance lateral and vertical characterization of heterogeneous samples at the cost of increasing complexity in the XPS data sets acquired. These imaging data sets require more sophisticated analysis methods than visual inspection if the data are to be interpreted effectively. Multivariate analysis (MVA) methods are increasingly utilized in surface spectroscopies to aid the analyst in interpreting the vast amount of information resulting from these multidimensional data set acquisitions. In this work, image processing analysis methods are tested on XPS data sets acquired from polymer blends. Images from the blends, acquired as a function of composition, time or energy, provide multidimensional data sets for algorithm evaluation. Multivariate image analysis (MIA) methods such as scatter diagrams, principal component analysis (PCA) and classification methods are used to extract maps of pure components from degradation and images-to-spectra data sets. In some cases the MVA results can be compared directly with the XPS spectra or images, which provide a critical reference point. This work will demonstrate that additional information can result from the application of MIA methods, even when direct spectral or image interpretation is possible.
Multispectral Imaging Development at ENST
1999
We present the development at ENST of a multispectral imaging system. Various methods have been implemented and tested for the characterisation of spectral camera sensitivity, the optimal choice of filters and the reconstruction of the spectral reflectance of the imaged surfaces. We first used a 4k-linear array camera with a set of large band filters. We are now experimenting with
Multispectral and Hyperspectral Imaging
The Encyclopedia of Archaeological Sciences, 2018
Since the invention of photography, a variety of approaches have made noninvasive imaging for cultural heritage applications possible. Multi‐ and hyperspectral imaging (together denoted spectral imaging) are two techniques that evolved from conventional color photography, having overcome its spectral limitations. Instead of imaging in three broad spectral bands, multispectral imaging acquires data in up to ten more or less equally wide and nonoverlapping spectral bands. Hyperspectral imaging goes beyond the multispectral approach by generating images in tens to hundreds of narrow, contiguous (i.e., adjacent but not overlapping) spectral bands. Most spectral imaging techniques are limited to the optical electromagnetic spectrum and acquire the reflected portion of the radiation that is used to illuminate the scene. However, imaging the emitted thermal radiation or active techniques based on laser scanners do exist as well. In cultural heritage, all these techniques are used to gain a better, noninvasive insight into the chemical and physical properties of the object(s) under investigation.
Multispectral Imaging Using Multiplexed Illumination
2007 IEEE 11th International Conference on Computer Vision, 2007
Many vision tasks such as scene segmentation, or the recognition of materials within a scene, become considerably easier when it is possible to measure the spectral reflectance of scene surfaces. In this paper, we present an efficient and robust approach for recovering spectral reflectance in a scene that combines the advantages of using multiple spectral sources and a multispectral camera. We have implemented a system based on this approach using a cluster of light sources with different spectra to illuminate the scene and a conventional RGB camera to acquire images. Rather than sequentially activating the sources, we have developed a novel technique to determine the optimal multiplexing sequence of spectral sources so as to minimize the number of acquired images. We use our recovered spectral measurements to recover the continuous spectral reflectance for each scene point by using a linear model for spectral reflectance. Our imaging system can produce multispectral videos of scenes at 30fps. We demonstrate the effectiveness of our system through extensive evaluation. As a demonstration, we present the results of applying data recovered by our system to material segmentation and spectral relighting.
Principles, Instrumentation, and Applications of Infrared Multispectral Imaging, An Overview
Analytical Letters, 2005
An infrared (IR) multispectral imaging spectrometer is an instrument that can simultaneously record infrared spectroscopic and spatial information of a sample. Chemical and physical properties of the sample can be elucidated from such images. In a multispectral imaging instrument, a camera is used to record the spatial distribution of the sample, and the spectral information is obtained with a dispersive device. This overview article describes operational principles and recent development of various components used in IR multispectral imaging instruments, including the electronic dispersive devices (acousto-optic tunable filter and liquid crystal tunable filter) and near-and middle-IR cameras (InGaAs, InSb, HgCdTe, and QWIP cameras). Recent applications and unique use of the IR imaging instruments will be described followed by discussion of the future prospects of the technique.