Overview of Experimental Setups in Spectroscopic Laboratory Measurements – the SpecTour Project

Jung, András; Götze, Christian; Gläßer, Cornelia

doi:10.1127/1432-8364/2012/0129

Cited by 11 publications

(7 citation statements)

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“…Their performance, however, is dependent on the many components of the imaging system, including illumination, optics, filters, dispersive gratings, sensor and signal processing, and also on operator choices relating to object positioning, calibration, file format and metadata [13]. Usually, each institution has its own unique set-up and specific workflow, which are dependent on the working principles of the acquiring system, and hence can significantly affect the information acquired for the same object [14]. As an example, the standard procedure in the National Museum in Krakow, Poland, involves a series of tasks requiring manual adjustment and judgement, as follows: This specificity not only makes it difficult to compare data from different systems, as it can influence the accuracy and reliability of the recorded information, but also causes some systems to be inappropriate for particular objects.…”

Section: Spectral Reflectance Image Capturementioning

confidence: 99%

Assessment of multispectral and hyperspectral imaging systems for digitisation of a Russian icon

et al. 2017

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In a study of multispectral and hyperspectral reflectance imaging, a Round Robin Test assessed the performance of different systems for the spectral digitisation of artworks. A Russian icon, mass-produced in Moscow in 1899, was digitised by ten institutions around Europe. The image quality was assessed by observers, and the reflectance spectra at selected points were reconstructed to characterise the icon's colourants and to obtain a quantitative estimate of accuracy. The differing spatial resolutions of the systems affected their ability to resolve fine details in the printed pattern. There was a surprisingly wide variation in the quality of imagery, caused by unwanted reflections from both glossy painted and metallic gold areas of the icon's surface. Specular reflection also degraded the accuracy of the reconstructed reflectance spectrum in some places, indicating the importance of control over the illumination geometry. Some devices that gave excellent results for matte colour charts proved to have poor performance for this demanding test object. There is a need for adoption of standards for digitising cultural heritage objects to achieve greater consistency of system performance and image quality.

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Section: Spectral Reflectance Image Capturementioning

confidence: 99%

Assessment of multispectral and hyperspectral imaging systems for digitisation of a Russian icon

et al. 2017

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“…The need for a standardized methodology for collecting-and assuring the quality of-field spectroscopy metadata has increased with the emergence of data sharing initiatives such as NASA's EOSDIS (Earth Science Data and Information System), the LTER (Long Term Ecological Research) network, the Australian Terrestrial Ecosystem Research Network (TERN), SpecNet [6] and some of the smaller ad hoc spectral libraries and databases created by remote sensing communities internationally. The absence of a formal standard prohibits efficient and viable intercomparison and fusibility of datasets generated from quantitative field observations [7]. This applies to data and metadata generated for discipline-agnostic information sharing systems and for discipline-specific databases [8].…”

Section: The Importance Of Field Spectroscopy Metadatamentioning

confidence: 99%

Assessing Field Spectroscopy Metadata Quality

et al. 2015

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This paper presents the proposed criteria for measuring the quality and completeness of field spectroscopy metadata in a spectral archive. Definitions for metadata quality and completeness for field spectroscopy datasets are introduced. Unique methods for measuring quality and completeness of metadata to meet the requirements of field spectroscopy datasets are presented. Field spectroscopy metadata quality can be defined in terms of (but is not limited to) logical consistency, lineage, semantic and syntactic error rates, compliance with a quality standard, quality assurance by a recognized authority, and reputational authority of the data owners/data creators. Two spectral libraries are examined as case studies of operationalized metadata policies, and the degree to which they are aligned with the needs of field spectroscopy scientists. The case studies reveal that the metadata in publicly available spectral datasets are underperforming on the quality and completeness measures. This paper is part two in a series examining the issues central to a metadata standard for field spectroscopy datasets.

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“…The metadata schema, taxonomies, and granularity of the metadata elements are determining factors in the interoperability between one metadata standard and another. The increasing volume of field spectroscopy datasets, from a broad variety of instruments, across research domains [1,[12][13][14] necessitates a framework for field spectroscopy metadata interoperability.…”

Section: The Importance Of Interoperable Field Spectroscopy Metadatasetsmentioning

confidence: 99%

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

et al. 2015

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This paper presents an approach to developing robust metadata standards for specific applications that serves to ensure a high level of reliability and interoperability for a spectroscopy dataset. The challenges of designing a metadata standard that meets the unique requirements of specific user communities are examined, including in situ measurement of reflectance underwater, using coral as a case in point. Metadata schema mappings from seven existing metadata standards demonstrate that they consistently fail to meet the needs of field spectroscopy scientists for general and specific applications (μ = 22%, σ = 32% conformance with the core metadata requirements and μ = 19%, σ = 18% for the special case of a benthic (e.g., coral) reflectance metadataset). Issues such as field measurement methods, instrument calibration, and data representativeness for marine field spectroscopy campaigns are investigated within the context of submerged benthic measurements. The implication of semantics and syntax for a robust and flexible metadata standard are also considered. A hybrid standard that serves as a "best of breed" incorporating useful modules and parameters within the standards is proposed. This paper is Part 3 in a series of papers in this journal, examining the issues central to a metadata standard for field spectroscopy datasets. The results presented in this paper are an important step towards field spectroscopy metadata standards that address the specific needs of field OPEN ACCESSRemote Sens. 2015, 7 15669 spectroscopy data stakeholders while facilitating dataset documentation, quality assurance, discoverability and data exchange within large-scale information sharing platforms.

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Overview of Experimental Setups in Spectroscopic Laboratory Measurements – the SpecTour Project

Cited by 11 publications

References 0 publications

Assessment of multispectral and hyperspectral imaging systems for digitisation of a Russian icon

Assessment of multispectral and hyperspectral imaging systems for digitisation of a Russian icon

Assessing Field Spectroscopy Metadata Quality

Towards an Interoperable Field Spectroscopy Metadata Standard with Extended Support for Marine Specific Applications

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