Articles liés à Image Segmentation and Compression Using Hidden Markov...
Synopsis
In the current age of information technology, the issues of distributing and utilizing images efficiently and effectively are of substantial concern. Solutions to many of the problems arising from these issues are provided by techniques of image processing, among which segmentation and compression are topics of this book.
Image segmentation is a process for dividing an image into its constituent parts. For block-based segmentation using statistical classification, an image is divided into blocks and a feature vector is formed for each block by grouping statistics of its pixel intensities. Conventional block-based segmentation algorithms classify each block separately, assuming independence of feature vectors.
Image Segmentation and Compression Using Hidden Markov Models presents a new algorithm that models the statistical dependence among image blocks by two dimensional hidden Markov models (HMMs). Formulas for estimating the model according to the maximum likelihood criterion are derived from the EM algorithm. To segment an image, optimal classes are searched jointly for all the blocks by the maximum a posteriori (MAP) rule. The 2-D HMM is extended to multiresolution so that more context information is exploited in classification and fast progressive segmentation schemes can be formed naturally.
The second issue addressed in the book is the design of joint compression and classification systems using the 2-D HMM and vector quantization. A classifier designed with the side goal of good compression often outperforms one aimed solely at classification because overfitting to training data is suppressed by vector quantization.
Image Segmentation and Compression Using Hidden Markov Models is an essential reference source for researchers and engineers working in statistical signal processing or image processing, especially those who are interested in hidden Markov models. It is also of value to those working on statistical modeling.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
- ÉditeurSpringer
- Date d'édition2000
- ISBN 10 0792378997
- ISBN 13 9780792378990
- ReliureRelié
- Langueanglais
- Nombre de pages141
- Coordonnées du fabricantnon disponible
Acheter neuf
Afficher cet article
EUR 136,16
EUR 9,70 expédition depuis Allemagne vers France
Destinations, frais et délais
Résultats de recherche pour Image Segmentation and Compression Using Hidden Markov...
Image d'archives
Image Segmentation and Compression Using Hidden Markov Models
Edité par
Springer US, 2000
ISBN 10 : 0792378997
ISBN 13 : 9780792378990
Ancien ou d'occasion
Couverture rigide
Vendeur : Buchpark, Trebbin, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Etat : Gut. Zustand: Gut | Seiten: 160 | Sprache: Englisch | Produktart: Bücher. N° de réf. du vendeur 1432255/3
Quantité disponible : 1 disponible(s)
Image d'archives
Image Segmentation and Compression Using Hidden Markov Models
Edité par
Springer, 2000
ISBN 10 : 0792378997
ISBN 13 : 9780792378990
Ancien ou d'occasion
Couverture rigide
Vendeur : Ammareal, Morangis, France
Évaluation du vendeur 5 sur 5 étoiles
Hardcover. Etat : Très bon. Ancien livre de bibliothèque. Edition 2000. Ammareal reverse jusqu'à 15% du prix net de cet article à des organisations caritatives. ENGLISH DESCRIPTION Book Condition: Used, Very good. Former library book. Edition 2000. Ammareal gives back up to 15% of this item's net price to charity organizations. N° de réf. du vendeur E-863-128
Quantité disponible : 1 disponible(s)
Image fournie par le vendeur
Image Segmentation and Compression Using Hidden Markov Models
impression à la demandeVendeur : moluna, Greven, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. In the current age of information technology, the issues of distributing and utilizing images efficiently and effectively are of substantial concern. Solutions to many of the problems arising from these issues are provided by techniques of image processi. N° de réf. du vendeur 5970520
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Image Segmentation and Compression Using Hidden Markov Models
Edité par
Springer US Aug 2000, 2000
ISBN 10 : 0792378997
ISBN 13 : 9780792378990
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -In the current age of information technology, the issues of distributing and utilizing images efficiently and effectively are of substantial concern. Solutions to many of the problems arising from these issues are provided by techniques of image processing, among which segmentation and compression are topics of this book. Image segmentation is a process for dividing an image into its constituent parts. For block-based segmentation using statistical classification, an image is divided into blocks and a feature vector is formed for each block by grouping statistics of its pixel intensities. Conventional block-based segmentation algorithms classify each block separately, assuming independence of feature vectors. Image Segmentation and Compression Using Hidden Markov Models presents a new algorithm that models the statistical dependence among image blocks by two dimensional hidden Markov models (HMMs). Formulas for estimating the model according to the maximum likelihood criterion are derived from the EM algorithm. To segment an image, optimal classes are searched jointly for all the blocks by the maximum a posteriori (MAP) rule. The 2-D HMM is extended to multiresolution so that more context information is exploited in classification and fast progressive segmentation schemes can be formed naturally. The second issue addressed in the book is the design of joint compression and classification systems using the 2-D HMM and vector quantization. A classifier designed with the side goal of good compression often outperforms one aimed solely at classification because overfitting to training data is suppressed by vector quantization. Image Segmentation and Compression Using Hidden Markov Models is an essential reference source for researchers and engineers working in statistical signal processing or image processing, especially those who are interested in hidden Markov models. It is also of value to those working on statistical modeling. 160 pp. Englisch. N° de réf. du vendeur 9780792378990
Quantité disponible : 2 disponible(s)
Image d'archives
Image Segmentation and Compression Using Hidden Markov Models (The Springer International Series in Engineering and Computer Science, 571)
Vendeur : Ria Christie Collections, Uxbridge, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. In. N° de réf. du vendeur ria9780792378990_new
Quantité disponible : Plus de 20 disponibles
Image fournie par le vendeur
Image Segmentation and Compression Using Hidden Markov Models
Edité par
Springer US, Springer US Aug 2000, 2000
ISBN 10 : 0792378997
ISBN 13 : 9780792378990
Neuf
Couverture rigide
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Neuware -In the current age of information technology, the issues of distributing and utilizing images efficiently and effectively are of substantial concern. Solutions to many of the problems arising from these issues are provided by techniques of image processing, among which segmentation and compression are topics of this book.Image segmentation is a process for dividing an image into its constituent parts. For block-based segmentation using statistical classification, an image is divided into blocks and a feature vector is formed for each block by grouping statistics of its pixel intensities. Conventional block-based segmentation algorithms classify each block separately, assuming independence of feature vectors.Image Segmentation and Compression Using Hidden Markov Models presents a new algorithm that models the statistical dependence among image blocks by two dimensional hidden Markov models (HMMs). Formulas for estimating the model according to the maximum likelihood criterion are derived from the EM algorithm. To segment an image, optimal classes are searched jointly for all the blocks by the maximum a posteriori (MAP) rule. The 2-D HMM is extended to multiresolution so that more context information is exploited in classification and fast progressive segmentation schemes can be formed naturally.The second issue addressed in the book is the design of joint compression and classification systems using the 2-D HMM and vector quantization. A classifier designed with the side goal of good compression often outperforms one aimed solely at classification because overfitting to training data is suppressed by vector quantization.Image Segmentation and Compression Using Hidden Markov Models is an essential reference source for researchers and engineers working in statistical signal processing or image processing, especially those who are interested in hidden Markov models. It is also of value to those working on statistical modeling.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 160 pp. Englisch. N° de réf. du vendeur 9780792378990
Quantité disponible : 2 disponible(s)
Image fournie par le vendeur
Image Segmentation and Compression Using Hidden Markov Models
Edité par
Springer US, Springer US, 2000
ISBN 10 : 0792378997
ISBN 13 : 9780792378990
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - In the current age of information technology, the issues of distributing and utilizing images efficiently and effectively are of substantial concern. Solutions to many of the problems arising from these issues are provided by techniques of image processing, among which segmentation and compression are topics of this book. Image segmentation is a process for dividing an image into its constituent parts. For block-based segmentation using statistical classification, an image is divided into blocks and a feature vector is formed for each block by grouping statistics of its pixel intensities. Conventional block-based segmentation algorithms classify each block separately, assuming independence of feature vectors. Image Segmentation and Compression Using Hidden Markov Models presents a new algorithm that models the statistical dependence among image blocks by two dimensional hidden Markov models (HMMs). Formulas for estimating the model according to the maximum likelihood criterion are derived from the EM algorithm. To segment an image, optimal classes are searched jointly for all the blocks by the maximum a posteriori (MAP) rule. The 2-D HMM is extended to multiresolution so that more context information is exploited in classification and fast progressive segmentation schemes can be formed naturally. The second issue addressed in the book is the design of joint compression and classification systems using the 2-D HMM and vector quantization. A classifier designed with the side goal of good compression often outperforms one aimed solely at classification because overfitting to training data is suppressed by vector quantization. Image Segmentation and Compression Using Hidden Markov Models is an essential reference source for researchers and engineers working in statistical signal processing or image processing, especially those who are interested in hidden Markov models. It is also of value to those working on statistical modeling. N° de réf. du vendeur 9780792378990
Quantité disponible : 1 disponible(s)
Image d'archives
Image Segmentation and Compression Using Hidden Markov Models (The Springer International Series in Engineering and Computer Science, 571)
Vendeur : Lucky's Textbooks, Dallas, TX, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. N° de réf. du vendeur ABLIING23Feb2416190184861
Quantité disponible : Plus de 20 disponibles
Image d'archives
Image Segmentation and Compression Using Hidden Markov Models
Vendeur : Books Puddle, New York, NY, Etats-Unis
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. pp. 160. N° de réf. du vendeur 263076521
Quantité disponible : 4 disponible(s)
Image d'archives
Image Segmentation and Compression Using Hidden Markov Models
impression à la demandeVendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 5 sur 5 étoiles
Etat : New. Print on Demand pp. 160 Illus. N° de réf. du vendeur 5852790
Quantité disponible : 4 disponible(s)