Overview
- Presents the recent state-of-the-art of geometrical multiresolution methods leading to sparse image representations
- Provides many open problems in the area of geometrical multiresolution methods of image approximation
- Includes competitive applications of geometrical multiresolution methods to image compression, denoising and edge detection
- Includes supplementary material: sn.pub/extras
Part of the book series: Studies in Computational Intelligence (SCI, volume 545)
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Table of contents (8 chapters)
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Front Matter
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Multismoothlet Transform
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Front Matter
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Applications
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Front Matter
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Back Matter
Keywords
About this book
Modern image processing techniques are based on multiresolution geometrical methods of image representation. These methods are efficient in sparse approximation of digital images. There is a wide family of functions called simply ‘X-lets’, and these methods can be divided into two groups: the adaptive and the nonadaptive. This book is devoted to the adaptive methods of image approximation, especially to multismoothlets.
Besides multismoothlets, several other new ideas are also covered. Current literature considers the black and white images with smooth horizon function as the model for sparse approximation but here, the class of blurred multihorizon is introduced, which is then used in the approximation of images with multiedges. Additionally, the semi-anisotropic model of multiedge representation, the introduction of the shift invariant multismoothlet transform and sliding multismoothlets are also covered.
Geometrical Multiresolution Adaptive Transforms should be accessible to both mathematicians and computer scientists. It is suitable as a professional reference for students, researchers and engineers, containing many open problems and will be an excellent starting point for those who are beginning new research in the area or who want to use geometrical multiresolution adaptive methods in image processing, analysis or compression.
Reviews
From the book reviews:
“The book is divided into two parts. The first part is devoted to the theory of multismoothlets. … The second part of the book is devoted to applications of the presented transforms. … The author gives many examples presenting the notations and problems considered, so it makes the learning easier. It is suitable for students, researchers and engineers interested in multiresolution representation of images and its applications.” (Krzystof Gdawiec, zbMATH, Vol. 1297, 2014)
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Geometrical Multiresolution Adaptive Transforms
Book Subtitle: Theory and Applications
Authors: Agnieszka Lisowska
Series Title: Studies in Computational Intelligence
DOI: https://doi.org/10.1007/978-3-319-05011-9
Publisher: Springer Cham
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-05010-2Published: 03 April 2014
Softcover ISBN: 978-3-319-37714-8Published: 03 September 2016
eBook ISBN: 978-3-319-05011-9Published: 24 March 2014
Series ISSN: 1860-949X
Series E-ISSN: 1860-9503
Edition Number: 1
Number of Pages: XII, 107
Number of Illustrations: 44 b/w illustrations, 21 illustrations in colour
Topics: Image Processing and Computer Vision, Math Applications in Computer Science, Mathematical Applications in Computer Science