Natural Image Statistics: A Probabilistic Approach to Early Computational Vision.
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
London
Springer London
2009
|
| Ausgabe: | 1st ed. 2009 |
| Schriftenreihe: | Computational Imaging and Vision
39 |
| Schlagworte: | |
| Online-Zugang: | DE-355 Volltext |
| Beschreibung: | 1 Online-Ressource (XIX, 448 Seiten) |
| ISBN: | 9781848824911 |
| DOI: | 10.1007/978-1-84882-491-1 |
Internformat
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| 505 | 8 | |a One of the most successful frameworks in computational neuroscience is modelling visual processing using the statistical structure of natural images. In this framework, the visual system of the brain constructs a model of the statistical regularities of the incoming visual data. This enables the visual system to perform efficient probabilistic inference. The same framework is also very useful in engineering applications such as image processing and computer vision. This book is the first comprehensive introduction to the multidisciplinary field of natural image statistics and its intention is to present a general theory of early vision and image processing in a manner that can be approached by readers from a variety of scientific backgrounds. A wealth of relevant background material is presented in the first section as an introduction to the subject. Following this are five unique sections, carefully selected so as to give a clear overview of all the basic theory, as well as the most recent developments and research. This structure, together with the included exercises and computer assignments, also make it an excellent textbook. Natural Image Statistics is a timely and valuable resource for advanced students and researchers in any discipline related to vision, such as neuroscience, computer science, psychology, electrical engineering, cognitive science or statistics | |
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Datensatz im Suchindex
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| author | Hyvärinen, Aapo Hurri, Jarmo Hoyer, Patrick O. |
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| contents | One of the most successful frameworks in computational neuroscience is modelling visual processing using the statistical structure of natural images. In this framework, the visual system of the brain constructs a model of the statistical regularities of the incoming visual data. This enables the visual system to perform efficient probabilistic inference. The same framework is also very useful in engineering applications such as image processing and computer vision. This book is the first comprehensive introduction to the multidisciplinary field of natural image statistics and its intention is to present a general theory of early vision and image processing in a manner that can be approached by readers from a variety of scientific backgrounds. A wealth of relevant background material is presented in the first section as an introduction to the subject. Following this are five unique sections, carefully selected so as to give a clear overview of all the basic theory, as well as the most recent developments and research. This structure, together with the included exercises and computer assignments, also make it an excellent textbook. Natural Image Statistics is a timely and valuable resource for advanced students and researchers in any discipline related to vision, such as neuroscience, computer science, psychology, electrical engineering, cognitive science or statistics |
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| dewey-full | 612.8 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 612 - Human physiology |
| dewey-raw | 612.8 |
| dewey-search | 612.8 |
| dewey-sort | 3612.8 |
| dewey-tens | 610 - Medicine and health |
| discipline | Medizin |
| doi_str_mv | 10.1007/978-1-84882-491-1 |
| edition | 1st ed. 2009 |
| format | Electronic eBook |
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| series2 | Computational Imaging and Vision |
| spelling | Hyvärinen, Aapo Verfasser aut Natural Image Statistics A Probabilistic Approach to Early Computational Vision. by Aapo Hyvärinen, Jarmo Hurri, Patrick O. Hoyer 1st ed. 2009 London Springer London 2009 1 Online-Ressource (XIX, 448 Seiten) txt rdacontent c rdamedia cr rdacarrier Computational Imaging and Vision 39 One of the most successful frameworks in computational neuroscience is modelling visual processing using the statistical structure of natural images. In this framework, the visual system of the brain constructs a model of the statistical regularities of the incoming visual data. This enables the visual system to perform efficient probabilistic inference. The same framework is also very useful in engineering applications such as image processing and computer vision. This book is the first comprehensive introduction to the multidisciplinary field of natural image statistics and its intention is to present a general theory of early vision and image processing in a manner that can be approached by readers from a variety of scientific backgrounds. A wealth of relevant background material is presented in the first section as an introduction to the subject. Following this are five unique sections, carefully selected so as to give a clear overview of all the basic theory, as well as the most recent developments and research. This structure, together with the included exercises and computer assignments, also make it an excellent textbook. Natural Image Statistics is a timely and valuable resource for advanced students and researchers in any discipline related to vision, such as neuroscience, computer science, psychology, electrical engineering, cognitive science or statistics Neuroscience Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Speech and Image Processing Neurosciences Image processing / Digital techniques Computer vision Signal processing Hurri, Jarmo aut Hoyer, Patrick O. aut Erscheint auch als Druck-Ausgabe 9781848824904 Erscheint auch als Druck-Ausgabe 9781848825031 Erscheint auch als Druck-Ausgabe 9781849968447 https://doi.org/10.1007/978-1-84882-491-1 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Hyvärinen, Aapo Hurri, Jarmo Hoyer, Patrick O. Natural Image Statistics A Probabilistic Approach to Early Computational Vision. One of the most successful frameworks in computational neuroscience is modelling visual processing using the statistical structure of natural images. In this framework, the visual system of the brain constructs a model of the statistical regularities of the incoming visual data. This enables the visual system to perform efficient probabilistic inference. The same framework is also very useful in engineering applications such as image processing and computer vision. This book is the first comprehensive introduction to the multidisciplinary field of natural image statistics and its intention is to present a general theory of early vision and image processing in a manner that can be approached by readers from a variety of scientific backgrounds. A wealth of relevant background material is presented in the first section as an introduction to the subject. Following this are five unique sections, carefully selected so as to give a clear overview of all the basic theory, as well as the most recent developments and research. This structure, together with the included exercises and computer assignments, also make it an excellent textbook. Natural Image Statistics is a timely and valuable resource for advanced students and researchers in any discipline related to vision, such as neuroscience, computer science, psychology, electrical engineering, cognitive science or statistics Neuroscience Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Speech and Image Processing Neurosciences Image processing / Digital techniques Computer vision Signal processing |
| title | Natural Image Statistics A Probabilistic Approach to Early Computational Vision. |
| title_auth | Natural Image Statistics A Probabilistic Approach to Early Computational Vision. |
| title_exact_search | Natural Image Statistics A Probabilistic Approach to Early Computational Vision. |
| title_full | Natural Image Statistics A Probabilistic Approach to Early Computational Vision. by Aapo Hyvärinen, Jarmo Hurri, Patrick O. Hoyer |
| title_fullStr | Natural Image Statistics A Probabilistic Approach to Early Computational Vision. by Aapo Hyvärinen, Jarmo Hurri, Patrick O. Hoyer |
| title_full_unstemmed | Natural Image Statistics A Probabilistic Approach to Early Computational Vision. by Aapo Hyvärinen, Jarmo Hurri, Patrick O. Hoyer |
| title_short | Natural Image Statistics |
| title_sort | natural image statistics a probabilistic approach to early computational vision |
| title_sub | A Probabilistic Approach to Early Computational Vision. |
| topic | Neuroscience Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Speech and Image Processing Neurosciences Image processing / Digital techniques Computer vision Signal processing |
| topic_facet | Neuroscience Computer Imaging, Vision, Pattern Recognition and Graphics Signal, Speech and Image Processing Neurosciences Image processing / Digital techniques Computer vision Signal processing |
| url | https://doi.org/10.1007/978-1-84882-491-1 |
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