Search results for "lcsh:TA1501-1820"

showing 5 items of 95 documents

Spectral imaging from UAVs under varying illumination conditions

2013

Abstract. Rapidly developing unmanned aerial vehicles (UAV) have provided the remote sensing community with a new rapidly deployable tool for small area monitoring. The progress of small payload UAVs has introduced greater demand for light weight aerial payloads. For applications requiring aerial images, a simple consumer camera provides acceptable data. For applications requiring more detailed spectral information about the surface, a new Fabry-Perot interferometer based spectral imaging technology has been developed. This new technology produces tens of successive images of the scene at different wavelength bands in very short time. These images can be assembled in spectral data cubes wit…

lcsh:Applied optics. Photonicsmedicine.medical_specialty010504 meteorology & atmospheric sciencesympäristöRemote sensing application0211 other engineering and technologiesIrradianceGeometryStereoscopy02 engineering and technologyradiometryEnvironmenthigh-resolution01 natural scienceslcsh:Technologylaw.inventionradiometriahyper spectrallawPhotogrammetriamedicineComputer vision021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensingfotogrammetrialuokitus (toiminta)Payloadbusiness.industrylcsh:Tlcsh:TA1501-1820korkea resoluutioClassificationSpectral imaginghyperspektriInterferometryGeographyPhotogrammetryluokittelulcsh:TA1-2040PhotogrammetryRadiometryArtificial intelligencegeometriabusinesslcsh:Engineering (General). Civil engineering (General)
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PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON

2018

Abstract. Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

lcsh:Applied optics. Photonicsmedicine.medical_specialtySoftware_GENERALhyperspectral imagingComputer sciencedata analysis0208 environmental biotechnologyImage processing02 engineering and technologykuvankäsittelylcsh:Technologyopen sourceavoin lähdekoodimedicinecomputer.programming_languagelcsh:Tbusiness.industrylcsh:TA1501-1820Hyperspectral imagingPython (programming language)Hyperspectral image processing020801 environmental engineeringSpectral imagingpythonkoneoppiminenlcsh:TA1-2040lcsh:Engineering (General). Civil engineering (General)businessSoftware engineeringcomputerAgile software developmentThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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SNAPSHOT SPECTRAL AND COLOR IMAGING USING A REGULAR DIGITAL CAMERA WITH A MONOCHROMATIC IMAGE SENSOR

2017

Spectral imaging (SI) refers to the acquisition of the three-dimensional (3D) spectral cube of spatial and spectral data of a source object at a limited number of wavelengths in a given wavelength range. Snapshot spectral imaging (SSI) refers to the instantaneous acquisition (in a single shot) of the spectral cube, a process suitable for fast changing objects. Known SSI devices exhibit large total track length (TTL), weight and production costs and relatively low optical throughput. We present a simple SSI camera based on a regular digital camera with (i) an added diffusing and dispersing phase-only static optical element at the entrance pupil (diffuser) and (ii) tailored compressed sensing…

lcsh:Applied optics. Photonicsmedicine.medical_specialtybusiness.product_categoryhyperspectral imagingComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION02 engineering and technologyimaging systemscomputational imaging01 natural scienceslcsh:Technology010309 opticsEntrance pupilComputational photographyOpticsColor gel0103 physical sciencesmultispectral imaging0202 electrical engineering electronic engineering information engineeringmedicineComputer visionImage sensorDigital camerabusiness.industryColor imagelcsh:Tlcsh:TA1501-1820Spectral imagingCompressed sensinglcsh:TA1-2040020201 artificial intelligence & image processingArtificial intelligenceMonochromatic colorbusinesslcsh:Engineering (General). Civil engineering (General)
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Comparison of a near-infrared reflectance spectroscopy system and skin conductance measurements for in vivo estimation of skin hydration: a clinical …

2017

Diffuse reflectance spectroscopy system was developed for estimation of skin hydration in the near-infrared spectral range of 900-1700 nm. Experimental setup consisted of a near-infrared spectrometer, Y-type fiber optics probe with 1 detection and 6 illumination fibers, halogen-tungsten light source and a PC. By analyzing diffuse reflectance spectrum, a parameter representing skin hydration by performing baseline correction and calculating the area under the 1450 nm water absorption maximum is proposed. A clinical study was performed acquiring data of skin hydration of 39 patients' forearm skin. Results of the developed system are compared to results obtained by a commercial device based on…

lcsh:Applied optics. PhotonicsspectroscopyskinOptical fiberlcsh:Medical technologyAcoustics and UltrasonicsDiffuse reflectance infrared fourier transformwaterBiomedical EngineeringAbsorption (skin)near-infraredlaw.inventionBiomaterialsOpticsIn vivolawSpectroscopySpectrometerintegumentary systembusiness.industryChemistryNear-infrared spectroscopylcsh:TA1501-1820Atomic and Molecular Physics and Opticslcsh:R855-855.5Diffuse reflectanceDiffuse reflectionbusinessabsorptionhydrationJournal of Biomedical Photonics & Engineering
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Fabrication-friendly polarization-sensitive plasmonic grating for optimal surface-enhanced Raman spectroscopy

2020

Plasmonic nanostructures are widely utilized in surface-enhanced Raman spectroscopy (SERS) from ultraviolet to near-infrared applications. Periodic nanoplasmonic systems such as plasmonic gratings are of great interest as SERS-active substrates due to their strong polarization dependence and ease of fabrication. In this work, we modelled a silver grating that manifests a subradiant plasmonic resonance as a dip in its reflectivity with significant near-field enhancement only for transverse-magnetic (TM) polarization of light. We investigated the role of its fill factor, commonly defined as a ratio between the width of the grating groove and the grating period, on the SERS enhancement. We des…

lcsh:Applied optics. Photonicssurface-enhanced Raman scatteringplasmonic gratingPhysics::OpticsPlasmonic gratinglcsh:TA1501-1820fill factorpintaplasmonitnanorakenteetFill factorplasmoniikkalcsh:QC350-467Surface-enhanced Raman scatteringPhysics::Atomic Physicslcsh:Optics. LightJournal of the European Optical Society-Rapid Publications
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