Hexagonal Image Processing : A Practical Approach
Language: English
Published by Springer, 2005
Series: Book 1 of 86 - Advances in Computer Vision and Pattern Recognition
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
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Add to basketItem description from seller
Druck auf Anfrage Neuware - Printed after ordering - This book provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, and presents a novel framework for hexagonal image processing (HIP) based on hierarchical aggregates.The strengths offered by hexagonal lattices over square lattices to define digital images are considerable:higher packing density uniform connectivity of points (pixels) in the lattice better angular resolution by virtue of having more nearest neighbours superlative representation of curves The utility of the HIP framework is shown by implementing several basic image processing techniques (for the spatial and frequency domain) and some applications. Theory and algorithms are covered as well as details such as accommodating hardware that support only images sampled on a square lattice.This fresh approach offers insight and workable know-how to both researchers and postgraduates.
Seller Inventory # 9781852339142
- Title
- Hexagonal Image Processing : A Practical Approach
- Author
- Jayanthi Sivaswamy
- Publisher
- Springer
- Publication year
- 2005
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 1852339144
- ISBN 13
- 9781852339142
- Item weight
- 524 grams
- Dimensions
- 241x160x20 mm
- Series
- Book 1 of 86: Advances in Computer Vision and Pattern Recognition
"Synopsis" may belong to another edition of this title.
From the Back Cover
Hexagonal Image Processing provides an introduction to the processing of hexagonally sampled images, includes a survey of the work done in the field, and presents a novel framework for hexagonal image processing (HIP) based on hierarchical aggregates.
Digital image processing is currently dominated by the use of square sampling lattices, however, hexagonal sampling lattices can also be used to define digital images. The strengths offered by hexagonal lattices over square lattices are considerable:
- higher packing density,
- uniform connectivity of points (pixels) in the lattice,
- better angular resolution by virtue of having more nearest neighbours, and
- superlative representation of curves.
The utility of the HIP framework is demonstrated by implementing several basic image processing techniques (for the spatial and frequency domain) and some applications. The HIP framework serves as a tool for comparing processing of images defined on a square vs hexagonal grid, to determine their relative merits and demerits. The theory and algorithms covered are supplemented by attention to practical details such as accommodating hardware that support only images sampled on a square lattice.
Including a Foreword written by Professor Narendra Ahuja, an eminent researcher in the field of Image Processing and Computer Vision, the book's fresh approach to the subject offers insight and workable know-how to both researchers and postgraduates.
"About the title" may belong to another edition of this title.
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