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Item Details
Title: ADAPTIVE IMAGE PROCESSING
A COMPUTATIONAL INTELLIGENCE PERSPECTIVE
By: Ling Guan, Stuart William Perry, Hau San Wong
Format: Electronic book text

List price: £126.00


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ISBN 10: 1420042262
ISBN 13: 9781420042269
Publisher: TAYLOR & FRANCIS INC
Pub. date: 21 December, 2001
Series: Image Processing Series
Pages: 288
Description: A complete index of CRC handbooks identifying specific volumes, titles and the page numbers necessary to locate the information required. It includes subjects, compounds and names of organisms from the fields of biomedical science, biology, chemistry, engineering and computer science and physics.
Synopsis: Adaptive image processing is one of the most important techniques in visual information processing, especially in early vision such as image restoration, filtering, enhancement, and segmentation. While existing books present some important aspects of the issue, there is not a single book that treats this problem from a viewpoint that is directly linked to human perception - until now. This reference treats adaptive image processing from a computational intelligence viewpoint, systematically and successfully, from theory to applications, using the synergies of neural networks, fuzzy logic, and evolutionary computation. Based on the fundamentals of human perception, this book gives a detailed account of computational intelligence methods and algorithms for adaptive image processing in regularization, edge detection, and early vision.Adaptive Image Processing: A Computational Intelligence Perspective consists of 8 chapters:Chapter 1 - Provides material of an introductory nature to describe the basic concepts and current state-of-the-art in the field of computational intelligence for image restoration and edge detectionChapter 2 - Gives a mathematical description of the restoration problem from the neural network perspective, and describes current algorithms based on this methodChapter 3 - Extends the algorithm presented in chapter 2 to implement adaptive constraint restoration methods for both spatially invariant and spatially variant degradationsChapter 4 - Utilizes a perceptually motivated image error measure to introduce novel restoration algorithmsChapter 5 - Examines how model-based neural networks can be used to solve image restoration problemsChapter 6 - Probes image restoration algorithms, making use of the principles of evolutionary computationChapter 7 - Explores the difficult concept of image restoration when insufficient knowledge of the degrading function is availableChapter 8 - Studies the subject of edge detection and characterization using model-based neural networksThe first to treat adaptive image processing from a computational intelligence perspective, this work provides an excellent reference in R&D practice to researchers and IT technologists, is most suitable for teaching image processing and applied neural network courses, and will be of equal value for technical managers and executives in industries where intelligent visual information processing is required.
Illustrations: 34 Halftones, black and white; 81 Illustrations, black and white
Publication: US
Imprint: CRC Press Inc
Returns: Non-returnable
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