Authors:
Very first book on this topic
Accessible to a wide audience from different disciplines
Topic is very timely and of increasing importance
Includes supplementary material: sn.pub/extras
Part of the book series: Computational Imaging and Vision (CIVI, volume 39)
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Table of contents (21 chapters)
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Front Matter
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Introduction
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Background
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Front Matter
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Statistics of Linear Features
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Front Matter
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Nonlinear Features and Dependency of Linear Features
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Front Matter
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Time, Color, and Stereo
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Front Matter
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About this book
Reviews
From the reviews:
“The authors did a wonderful job of introducing the field of natural image statistics, comprehensively. The book provides the underlying fundamental mathematics … accessible to a wide audience. … provides exercises and computer assignments at the end of the chapters. … the advanced topics are treated in a similar manner to basic theory, makes the book suitable to be used as a textbook for advanced students and by researchers in any discipline related to computer vision.” (Michael Goldberg and R. Goldberg, ACM Computing Reviews, October, 2010)Bibliographic Information
Book Title: Natural Image Statistics
Book Subtitle: A Probabilistic Approach to Early Computational Vision.
Authors: Aapo Hyvärinen, Jarmo Hurri, Patrik O. Hoyer
Series Title: Computational Imaging and Vision
DOI: https://doi.org/10.1007/978-1-84882-491-1
Publisher: Springer London
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer-Verlag London 2009
Hardcover ISBN: 978-1-84882-490-4Published: 05 June 2009
Softcover ISBN: 978-1-84996-844-7Published: 22 October 2010
eBook ISBN: 978-1-84882-491-1Published: 21 April 2009
Series ISSN: 1381-6446
Edition Number: 1
Number of Pages: XIX, 448
Topics: Neurosciences, Computer Imaging, Vision, Pattern Recognition and Graphics, Signal, Image and Speech Processing