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020 _a9781447146520
_9978-1-4471-4652-0
024 7 _a10.1007/978-1-4471-4652-0
_2doi
050 4 _aQ337.5
050 4 _aTK7882.P3
072 7 _aUYQP
_2bicssc
072 7 _aCOM016000
_2bisacsh
082 0 4 _a006.4
_223
100 1 _aRobles-Kelly, Antonio.
_eauthor.
245 1 0 _aImaging Spectroscopy for Scene Analysis
_h[electronic resource] /
_cby Antonio Robles-Kelly, Cong Phuoc Huynh.
264 1 _aLondon :
_bSpringer London :
_bImprint: Springer,
_c2013.
300 _aXVIII, 270 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aAdvances in Computer Vision and Pattern Recognition,
_x2191-6586
505 0 _aIntroduction -- Spectral Image Acquisition -- Spectral Image Formation Process -- Reflectance Modelling -- Illuminant Power Spectrum -- Photometric Invariance -- Spectrum Representation -- Material Discovery -- Reflection Geometry -- Polarisation of Light -- Shape and Refractive Index from Polarisation.
520 _aIn contrast with trichromatic image sensors, imaging spectroscopy can capture the properties of the materials in a scene. This implies that scene analysis using imaging spectroscopy has the capacity to robustly encode material signatures, infer object composition and recover photometric parameters. This landmark text/reference presents a detailed analysis of spectral imaging, describing how it can be used in elegant and efficient ways for the purposes of material identification, object recognition and scene understanding. The opportunities and challenges of combining spatial and spectral information are explored in depth, as are a wide range of applications from surveillance and computational photography, to biosecurity and resource exploration. Topics and features: Discusses spectral image acquisition by hyperspectral cameras, and the process of spectral image formation Examines models of surface reflectance, the recovery of photometric invariants, and the estimation of the illuminant power spectrum from spectral imagery Describes spectrum representations for the interpolation of reflectance and radiance values, and the classification of spectra Reviews the use of imaging spectroscopy for material identification Explores the recovery of reflection geometry from image reflectance Investigates spectro-polarimetric imagery, and the recovery of object shape and material properties using polarimetric images captured from a single view An essential resource for researchers and graduate students of computer vision and pattern recognition, this comprehensive introduction to imaging spectroscopy for scene analysis will also be of great use to practitioners interested in shape analysis employing polarimetric imaging, and material recognition and classification using hyperspectral or multispectral data.
650 0 _aComputer science.
650 0 _aImage processing.
650 0 _aPattern recognition.
650 1 4 _aComputer Science.
650 2 4 _aPattern Recognition.
650 2 4 _aImage Processing and Computer Vision.
700 1 _aHuynh, Cong Phuoc.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781447146513
830 0 _aAdvances in Computer Vision and Pattern Recognition,
_x2191-6586
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4471-4652-0
912 _aZDB-2-SCS
942 _cEBK
999 _c52942
_d52942