Articles liés à Hyperspectral Image Generation, Processing and Analysis

Hyperspectral Image Generation, Processing and Analysis - Couverture souple

Muhammed, Hamed Hamid

 
9783838319735: Hyperspectral Image Generation, Processing and Analysis
Couverture souple
ISBN 10 : 3838319737 ISBN 13 : 9783838319735
Editeur : LAP LAMBERT Academic Publishing, 2009

Synopsis

Hyperspectral imaging is utilised in many applications, where measured data are processed, interpreted and converted into physical, chemical and/or biological properties of the target objects and/or processes being studied. In this thesis, various methods were proposed and applied to crop reflectance data (acquired by hand-held spectrometers) to detect, characterise and quantify disease severity and plant density. Furthermore, various surface water quality parameters of inland waters have been monitored using hyperspectral images acquired by airborne systems. However, the large size of these images raises the need for efficient data reduction. A new type of self- organising weighted neural networks was proposed and used for efficient reduction, mapping and clustering of large high-dimensional data sets, such as hyperspectral images. Finally, the analysis can be reversed to generate high resolution spectra from simpler measurements using multiple colour-filter mosaics, as suggested in the thesis. The acquired instantaneous image is demosaicked to generate a multi-band image that can finally be transformed into a hyperspectral image.

Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.

Présentation de l'éditeur

Hyperspectral imaging is utilised in many applications, where measured data are processed, interpreted and converted into physical, chemical and/or biological properties of the target objects and/or processes being studied. In this thesis, various methods were proposed and applied to crop reflectance data (acquired by hand-held spectrometers) to detect, characterise and quantify disease severity and plant density. Furthermore, various surface water quality parameters of inland waters have been monitored using hyperspectral images acquired by airborne systems. However, the large size of these images raises the need for efficient data reduction. A new type of self- organising weighted neural networks was proposed and used for efficient reduction, mapping and clustering of large high-dimensional data sets, such as hyperspectral images. Finally, the analysis can be reversed to generate high resolution spectra from simpler measurements using multiple colour-filter mosaics, as suggested in the thesis. The acquired instantaneous image is demosaicked to generate a multi-band image that can finally be transformed into a hyperspectral image.

Biographie de l'auteur

PhD in Computerised Image Analysis (2005), Assistant Professor, Medical Image Processing and Analysis, Royal Institute of Technology, Sweden. Recipient of the Benzelius prize (an internationally recognized scientific award for young researchers), Royal Society of Sciences in Uppsala (Kungliga Vetenskaps-Societen), Uppsala, Sweden, 2006.

Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.

Éditeur
LAP LAMBERT Academic Publishing
Date d'édition
2009
Langue
anglais
ISBN 10 
3838319737
ISBN 13 
9783838319735
Reliure
Broché
Nombre de pages
64
Coordonnées du fabricant
non disponible
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