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e-Book Adaptive Image Processing: A Computational Intelligence Perspective (Image Processing Series) download

e-Book Adaptive Image Processing: A Computational Intelligence Perspective (Image Processing Series) download

by Ling Guan,Hau San Wong,Stuart William Perry

ISBN: 0849302838
ISBN13: 978-0849302831
Language: English
Publisher: CRC Press; 1 edition (December 21, 2001)
Pages: 288
Category: Computer Science
Subategory: Technologies

ePub size: 1393 kb
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Series: Image processing series. File: PDF, . 6 MB. Czytaj online.

Series: Image processing series.

A new technique in visual query processing and visualization in 2D space. New experiments and updates on perceptual error-based restoration.

Adaptive image processing is one of the most important techniques in visual information processing, especially in early vision .

ByKim-Hui Yap, Ling Guan, Stuart William Perry, Hau San Wong. First Published 2010. eBook Published 3 October 2018. Pub. location Boca Raton.

Fundamentals; spatially adaptive image restoration; perceptually motivated image restoration; model-based adaptive image restoration; adaptive regularization using evolutionary computation; blind image deconvulsion; edge detection using model-based neural networks.

Title: Adaptive image processing: a computational intelligence perspective. Publisher: CRC Press. Series: Image Processing Series. Author: Ling Guan, Stuart William Perry, Hau San Wong. Year: published in 2001. Summary: Application Of Computational Intelligence Techniques – Often Called Soft Computing – To The Problem Of Adaptive Image Processing Is The Focus Of This Text.

ed. of: Adaptive image processing : a computational intelligence perspective, Stuart William Perry, Hau-San Wong, Ling Guan. Includes bibliographical references and index.

By Kim-Hui Yap, Ling Guan, Stuart William Perry, Hau San Wong. 376 pages 253 B/W Illus.

A Computational Intelligence Perspective Stuart William Perry Hau-San Wong Ling Guan. Preface In this book, we consider the application of computational intelligence techniques to the problem of adaptive image processing. CRC PR E S S Boca Raton London New York Washington, . Perry, Stuart William. In adaptive image processing, it is usually required to identify each image pixel with a particular feature type (e. smooth regions, edges, textures, et. for separate processing, which constitutes a segmentation problem.

Kim-Hui Yap, Ling Guan, Stuart William Perry, Hau San Wong. Category: Математика, Вычислительная математика. Adaptive image processing: a computational intelligence perspective. Ling Guan, Stuart William Perry, Hau San Wong. Category: Computer science, Image processing. 9 Mb. Category: Computer science.

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.
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