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About this book
Computer vision has progressed considerably over recent years. From methods only applicable to simple images, it has developed to deal with increasingly complex scenes, volumes and time sequences. A substantial part of this book deals with the problem of designing models that can be used for several purposes within computer vision. These partial models have some general properties of invariance generation and generality in model generation.
Signal Processing for Computer Vision is the first book to give a unified treatment of representation and filtering of higher order data, such as vectors and tensors in multidimensional space. Included is a systematic organisation for the implementation of complex models in a hierarchical modular structure and novel material on adaptive filtering using tensor data representation.
Signal Processing for Computer Vision is intended for final year undergraduate and graduate students as well as engineers and researchers in the field of computer vision and image processing.
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Table of contents (13 chapters)
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Bibliographic Information
Book Title: Signal Processing for Computer Vision
Authors: Gösta H. Granlund, Hans Knutsson
DOI: https://doi.org/10.1007/978-1-4757-2377-9
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media Dordrecht 1995
Hardcover ISBN: 978-0-7923-9530-0Published: 31 December 1994
Softcover ISBN: 978-1-4419-5151-9Published: 07 December 2010
eBook ISBN: 978-1-4757-2377-9Published: 09 March 2013
Edition Number: 1
Number of Pages: XII, 437
Number of Illustrations: 297 b/w illustrations, 17 illustrations in colour
Topics: Signal, Image and Speech Processing, Computer Imaging, Vision, Pattern Recognition and Graphics, Image Processing and Computer Vision, Electrical Engineering