Artículos relacionados a Hyperspectral Image Generation, Processing and Analysis

Hyperspectral Image Generation, Processing and Analysis - Tapa blanda

Muhammed, Hamed Hamid

 
9783838319735: Hyperspectral Image Generation, Processing and Analysis
Tapa blanda
ISBN 10: 3838319737 ISBN 13: 9783838319735
Editorial: LAP LAMBERT Academic Publishing, 2009

Sinopsis

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.

"Sinopsis" puede pertenecer a otra edición de este libro.

Reseña del editor

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.

Biografía del autor

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.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
LAP LAMBERT Academic Publishing
Año de publicación
2009
Idioma
Inglés
ISBN 10 
3838319737
ISBN 13 
9783838319735
Encuadernación
Tapa blanda
Número de páginas
64
Contacto del fabricante
no disponible
Persona responsable
no disponible