Search results for "Spectral imaging"

showing 10 items of 311 documents

Tree species recognition in species rich area using UAV-borne hyperspectral imagery and stereo-photogrammetric point cloud

2017

Abstract. Recognition of tree species and geospatial information of tree species composition is essential for forest management. In this study we test tree species recognition using hyperspectral imagery from VNIR and SWIR camera sensors in combination with 3D photogrammetric canopy surface model based on RGB camera stereo-imagery. An arboretum forest with a high number of tree species was used as a test area. The imagery was acquired from the test area using UAV-borne cameras. Hyperspectral imagery was calibrated for providing a radiometrically corrected reflectance mosaic, which was tested along with the original uncalibrated imagery. Alternative estimators were tested for predicting tree…

lcsh:Applied optics. Photonicshyperspectral imaging0211 other engineering and technologiesPoint cloud02 engineering and technologyUAVslcsh:TechnologyImage sensor021101 geological & geomatics engineeringRemote sensing040101 forestryPixellcsh:Ttree species recognitionlcsh:TA1501-1820Hyperspectral imaging04 agricultural and veterinary sciencesOtaNanoVNIRTree (data structure)GeographyPhotogrammetryphotogrammetric point cloudlcsh:TA1-2040stereo-photogrammetry0401 agriculture forestry and fisheriesRGB color modellcsh:Engineering (General). Civil engineering (General)
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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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Updating strategies for distance based classification model with recursive least squares

2022

Abstract. The idea is to create a self-learning Minimal Learning Machine (MLM) model that is computationally efficient, easy to implement and performs with high accuracy. The study has two hypotheses. Experiment A examines the possibilities of introducing new classes with Recursive Least Squares (RLS) updates for the pre-trained self learning-MLM model. The idea of experiment B is to simulate the push broom spectral imagers working principles, update and test the model based on a stream of pixel spectrum lines on a continuous scanning process. Experiment B aims to train the model with a significantly small amount of labelled reference points and update it continuously with (RLS) to reach ma…

luokitus (toiminta)Minimal Learning Machinemachine learningkoneoppiminenclassificationhyperspectral imagingkaukokartoitusRecursive Least Squaresreal-time computationhyperspektrikuvantaminen
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Challenges in the use of Near Infrared Spectroscopy for improving wood quality: A review

2018

Aims of study: Forestry-related companies require quality monitoring methods capable to pass a large number of samples. This review paper is dealing with the utilization of near infrared (NIR) technique for wood analysis.Area of study: We have a global point of view for NIR applications and characterization of different kind of wood species is considered.Material and methods: NIR spectroscopy is a fast, non-destructive technique, applicable to any biological material, demanding little or no sample preparation. NIR spectroscopy and multivariate analysis serve well in laboratories where the conditions are controlled. The main challenges to NIR spectroscopy technique in field conditions are mo…

media_common.quotation_subjectSoil Science02 engineering and technologypulpmoistureQuality (business)lcsh:ForestryEcology Evolution Behavior and Systematicscamera hyperspectral genetic studiesmedia_commonRemote sensing040101 forestryNear Infrared Spectroscopy; wood properties; moisture; pulp; camera hyperspectral genetic studiesNear-infrared spectroscopyHyperspectral imagingForestryNear Infrared Spectroscopy04 agricultural and veterinary scienceswood properties021001 nanoscience & nanotechnologyBiological materialsLow noiseCharacterization (materials science)lcsh:SD1-669.50401 agriculture forestry and fisheriesEnvironmental scienceNir spectra0210 nano-technologyField conditionsForest Systems
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Semi-automatic detection of skin malformations by analysis of spectral images

2013

The multi-spectral imaging technique to reveal skin malformations has been described in this work. Four spectral images taken at polarized monochromatic LED illumination (450nm, 545nm, 660nm and 940 nm) and polarized white LED light imaged by CMOS sensor via cross-oriented polarizing filter were analyzed to calculate chromophore maps. The algorithm based on skin color analysis and user-defined threshold selection allows highlighting of skin areas with predefined chromophore concentration semi-automatically. Preliminary results of clinical tests are presented.

medicine.medical_specialtyCMOS sensorMaterials sciencebusiness.industryMultispectral imageImage segmentationPolarizing filterChromophorePolarizerlaw.inventionSpectral imagingOpticslawmedicineMonochromatic colorbusiness
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Snapshot multi-spectral-line imaging for applications in dermatology and forensics

2019

Performance of multi-spectral imaging critically depends on image acquisition time and working spectral bandwidths. Ultimate performance can be achieved if a set of monochromatic (single-wavelength) spectral images is obtained by a single snapshot - a technique provisionally called “snapshot multi-spectral-line imaging” or SMSLI. The SMSLI principle and the developed prototype devices for 3, 4 and 5 spectral line snapshot imaging are described. Two potential practical applications of SMSLI are discussed – for fast mapping of the main in-vivo skin chromophores and for detection of counterfeit banknotes and documents.

medicine.medical_specialtyComputer sciencebusiness.industryComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMulti spectralSpectral lineSpectral imagingmedicineImage acquisitionSnapshot (computer storage)Computer visionMonochromatic colorArtificial intelligencebusinessImaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues XVII
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Laser illumination designs for snapshot multi-spectral-line imaging

2019

For multi-spectral imaging, both acquisition time of the spectral image set and the spectral bandwidth of each image have to be minimized. Ultimate performance can be achieved if the set of monochromatic (single-wavelength) spectral images is obtained with a single snapshot — a technique provisionally called "snapshot multi-spectral-line imaging" or SMSLI. Using contemporary RGB colour cameras, up to three spectral line images can be extracted from a snapshot image data cube at specific illumination that comprises only three spectral lines, each of them positioned within one of the detection bands (R, G or B) [1]. Techniques able to provide more spectral line images are under development, a…

medicine.medical_specialtyComputer sciencebusiness.industryData_MISCELLANEOUSMultispectral imageComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONLaser01 natural sciencesSpectral linelaw.inventionSpectral imaging010309 opticsData cubeOpticslawComputer Science::Computer Vision and Pattern Recognition0103 physical sciencesmedicineRGB color modelSnapshot (computer storage)Monochromatic colorbusiness
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Single snapshot RGB multispectral imaging at fixed wavelengths: proof of concept

2014

A concept of single snapshot multispectral imaging by standard RGB image sensors under spectrally-specific illumination comprising a fixed number of narrow spectral lines is discussed and experimentally validated. The limiting conditions, RGB band spectral crosstalk corrections and potential applications for parametric mapping of skin are regarded, along with the preliminary results of the proof-of-concept measurements.

medicine.medical_specialtyComputer sciencebusiness.industryMultispectral imageSpectral lineSpectral imagingWavelengthOpticsProof of conceptComputer Science::Computer Vision and Pattern RecognitionmedicineRGB color modelSnapshot (computer storage)businessParametric statisticsSPIE Proceedings
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