Items related to Image Segmentation and Compression Using Hidden Markov...
Image Segmentation and Compression Using Hidden Markov Models: 571 (The Springer International Series in Engineering and Computer Science, 571) - Hardcover
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.
"synopsis" may belong to another edition of this title.
- PublisherSpringer
- Publication date2000
- ISBN 10 0792378997
- ISBN 13 9780792378990
- BindingHardcover
- LanguageEnglish
- Number of pages154
Search results for Image Segmentation and Compression Using Hidden Markov...
Stock Image
Image Segmentation and Compression Using Hidden Markov Models
Seller: Ammareal, Morangis, France
Seller rating 5 out of 5 stars
Hardcover. Condition: 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. Seller Inventory # E-863-128
Quantity: 1 available
Stock Image
Image Segmentation and Compression Using Hidden Markov Models
Seller: Buchpark, Trebbin, Germany
Seller rating 5 out of 5 stars
Condition: Gut. Zustand: Gut - Gebrauchs- und Lagerspuren. | Seiten: 160 | Sprache: Englisch | Produktart: Bücher. Seller Inventory # 1432255/3
Quantity: 1 available
Stock Image
Image Segmentation and Compression Using Hidden Markov Models (The Springer International Series in Engineering and Computer Science, 571)
Seller: Lucky's Textbooks, Dallas, TX, U.S.A.
Seller rating 5 out of 5 stars
Condition: New. Seller Inventory # ABLIING23Feb2416190184861
Quantity: Over 20 available
Stock Image
Image Segmentation and Compression Using Hidden Markov Models (The Springer International Series in Engineering and Computer Science, 571)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In. Seller Inventory # ria9780792378990_new
Quantity: Over 20 available
Seller Image
Image Segmentation and Compression Using Hidden Markov Models
Print on DemandSeller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Buch. Condition: 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. Seller Inventory # 9780792378990
Quantity: 2 available
Seller Image
Image Segmentation and Compression Using Hidden Markov Models
Print on DemandSeller: moluna, Greven, Germany
Seller rating 5 out of 5 stars
Gebunden. Condition: 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. Seller Inventory # 5970520
Quantity: Over 20 available
Seller Image
Image Segmentation and Compression Using Hidden Markov Models
Published by
Springer US, Springer US, 2000
ISBN 10: 0792378997
ISBN 13: 9780792378990
New
Hardcover
Seller: AHA-BUCH GmbH, Einbeck, Germany
Seller rating 5 out of 5 stars
Buch. Condition: 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. Seller Inventory # 9780792378990
Quantity: 1 available
Stock Image
Image Segmentation and Compression Using Hidden Markov Models (The Springer International Series in Engineering and Computer Science)
Seller: Mispah books, Redhill, SURRE, United Kingdom
Seller rating 4 out of 5 stars
Hardcover. Condition: Like New. Like New. book. Seller Inventory # ERICA79007923789976
Quantity: 1 available