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Hyperspectral Data Compression And Red Edge Indices: The Effect of Lossy Image Compression for Hyperspectral Data in Retrieving Red Edge Indices - Couverture souple
Synopsis
Lossy hyperspectral image compression techniques are widely used to solve the problems of data size. In this book, we evaluate lossy vector quantization and JPEG2000 hyperspectral data compression algorithms using red edge indices as end-products that we want to retrieve from our data. Two airborne hyperspectral data-sets for vegetated areas were tested, one acquired from (AISA) sensor for area in Tambisan, Malaysia and the other data-set acquired from (Hyspex) sensor for agriculture area in Norway. Two red edge products: Vogelmann1 and NDVI red edge indices were retrieved from each original data cube and from their decompressed data cubes. The standard deviation of percentage difference between a product retrieved from an original data cube and that from its decompressed data cube was used as a measure to quantify the impact of compression on end products. The minimum, maximum and average values of the original and compressed data were also used to quantify the differences in the red edge products.
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Présentation de l'éditeur
Lossy hyperspectral image compression techniques are widely used to solve the problems of data size. In this book, we evaluate lossy vector quantization and JPEG2000 hyperspectral data compression algorithms using red edge indices as end-products that we want to retrieve from our data. Two airborne hyperspectral data-sets for vegetated areas were tested, one acquired from (AISA) sensor for area in Tambisan, Malaysia and the other data-set acquired from (Hyspex) sensor for agriculture area in Norway. Two red edge products: Vogelmann1 and NDVI red edge indices were retrieved from each original data cube and from their decompressed data cubes. The standard deviation of percentage difference between a product retrieved from an original data cube and that from its decompressed data cube was used as a measure to quantify the impact of compression on end products. The minimum, maximum and average values of the original and compressed data were also used to quantify the differences in the red edge products.
Biographie de l'auteur
I graduated from the University of Jordan with a BSc in Computer Information Systems in 2006. After that i did my MSc in GIS and Remote Sensing from University Putra Malaysia 2008. Currently I am PhD student in the Computer Vision Lab at the Multimedia Department in University Putra Malaysia.
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Hyperspectral Data Compression And Red Edge Indices
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3845472227
ISBN 13 : 9783845472225
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Alomari AbdallahI graduated from the University of Jordan with a BSc in Computer Information Systems in 2006. After that i did my MSc in GIS and Remote Sensing from University Putra Malaysia 2008. Currently I am PhD student in the Co. N° de réf. du vendeur 5484012
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Hyperspectral Data Compression And Red Edge Indices : The Effect of Lossy Image Compression for Hyperspectral Data in Retrieving Red Edge Indices
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3845472227
ISBN 13 : 9783845472225
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Lossy hyperspectral image compression techniques are widely used to solve the problems of data size. In this book, we evaluate lossy vector quantization and JPEG2000 hyperspectral data compression algorithms using red edge indices as end-products that we want to retrieve from our data. Two airborne hyperspectral data-sets for vegetated areas were tested, one acquired from (AISA) sensor for area in Tambisan, Malaysia and the other data-set acquired from (Hyspex) sensor for agriculture area in Norway. Two red edge products: Vogelmann1 and NDVI red edge indices were retrieved from each original data cube and from their decompressed data cubes. The standard deviation of percentage difference between a product retrieved from an original data cube and that from its decompressed data cube was used as a measure to quantify the impact of compression on end products. The minimum, maximum and average values of the original and compressed data were also used to quantify the differences in the red edge products. N° de réf. du vendeur 9783845472225
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Hyperspectral Data Compression And Red Edge Indices
Edité par
LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10 : 3845472227
ISBN 13 : 9783845472225
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Lossy hyperspectral image compression techniques are widely used to solve the problems of data size. In this book, we evaluate lossy vector quantization and JPEG2000 hyperspectral data compression algorithms using red edge indices as end-products that we want to retrieve from our data. Two airborne hyperspectral data-sets for vegetated areas were tested, one acquired from (AISA) sensor for area in Tambisan, Malaysia and the other data-set acquired from (Hyspex) sensor for agriculture area in Norway. Two red edge products: Vogelmann1 and NDVI red edge indices were retrieved from each original data cube and from their decompressed data cubes. The standard deviation of percentage difference between a product retrieved from an original data cube and that from its decompressed data cube was used as a measure to quantify the impact of compression on end products. The minimum, maximum and average values of the original and compressed data were also used to quantify the differences in the red edge products. 88 pp. Englisch. N° de réf. du vendeur 9783845472225
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Hyperspectral Data Compression And Red Edge Indices
Edité par
LAP LAMBERT Academic Publishing Sep 2011, 2011
ISBN 10 : 3845472227
ISBN 13 : 9783845472225
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. Neuware -Lossy hyperspectral image compression techniques are widely used to solve the problems of data size. In this book, we evaluate lossy vector quantization and JPEG2000 hyperspectral data compression algorithms using red edge indices as end-products that we want to retrieve from our data. Two airborne hyperspectral data-sets for vegetated areas were tested, one acquired from (AISA) sensor for area in Tambisan, Malaysia and the other data-set acquired from (Hyspex) sensor for agriculture area in Norway. Two red edge products: Vogelmann1 and NDVI red edge indices were retrieved from each original data cube and from their decompressed data cubes. The standard deviation of percentage difference between a product retrieved from an original data cube and that from its decompressed data cube was used as a measure to quantify the impact of compression on end products. The minimum, maximum and average values of the original and compressed data were also used to quantify the differences in the red edge products.Books on Demand GmbH, Überseering 33, 22297 Hamburg 88 pp. Englisch. N° de réf. du vendeur 9783845472225
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Hyperspectral Data Compression And Red Edge Indices: The Effect of Lossy Image Compression for Hyperspectral Data in Retrieving Red Edge Indices
Edité par
LAP LAMBERT Academic Publishing, 2011
ISBN 10 : 3845472227
ISBN 13 : 9783845472225
Ancien ou d'occasion
Paperback
Vendeur : Mispah books, Redhill, SURRE, Royaume-Uni
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Paperback. Etat : Like New. Like New. book. N° de réf. du vendeur ERICA79638454722276
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