Adaptive image processing : a computational intelligence perspective /: a computational intelligence perspective. (©2010)

• Record Type: Book
• Further Information: Note: Kim-Hui Yap [and others].
• Other Names: Yap, Kim Hui; Perry, Stuart William
• Contents: Introduction; Importance of Vision; Adaptive Image Processing; Three Main Image Feature Classes; Difficulties in Adaptive Image-Processing System Design; Computational Intelligence Techniques; Scope of the Book; Contributions of the Current Work; Overview of This Book; Fundamentals of CI-Inspired Adaptive Image Restoration; Image Distortions; Image Restoration; Constrained Least Square Error; Neural Network Restoration; Neural Network Restoration Algorithms in the Literature; An Improved Algorithm; Analysis; Implementation Considerations; Numerical Study of the Algorithms; Summary; Spatially Adaptive Image Restoration; Dealing with Spatially Variant Distortion; Adaptive Constraint Extension of the Penalty Function Model; Correcting Spatially Variant Distortion Using Adaptive Constraints; Semiblind Restoration Using Adaptive Constraints; Implementation Considerations; More Numerical Examples; Numerical Examples; Local Variance Extension of the Lagrange Model; Summary; Acknowledgments; Regional Training Set Definition; Determination of the Image Partition; Edge-Texture Characterization Measure; ETC Fuzzy HMBNN for Adaptive Regularization; Theory of Fuzzy Sets; Edge-Texture Fuzzy Model Based on ETC Measure; Architecture of the Fuzzy HMBNN; Estimation of the Desired Network Output; Fuzzy Prediction of Desired Gray-Level Value; Experimental Results; Summary; Adaptive Regularization Using Evolutionary Computation; Introduction to Evolutionary Computation; ETC-pdf Image Model; Adaptive Regularization Using Evolutionary Programming; Experimental Results; Other Evolutionary Approaches for Image Restoration; Summary; Blind Image Deconvolution; Computational Reinforced Learning; Soft-Decision Method; Simulation Examples; Conclusions; Edge Detection Using Model-Based Neural Networks; MBNN Model for Edge Characterization; Network Architecture; Training Stage; Recognition Stage; Experimental Results; Summary; Image Analysis and Retrieval via Self-Organization; Self-Organizing Map (SOM); Self-Organizing Tree Map (SOTM); SOTM in Impulse Noise Removal; SOTM in Content-Based Retrieval; Genetic Optimization of Feature Representation for Compressed-Domain Image Categorization; Compressed-Domain Representation; Problem Formulation; Multiple-Classifier Approach; Experimental Results; Conclusion; Content-Based Image Retrieval Using Computational Intelligence Techniques; Problem Description and Formulation; Soft Relevance Feedback in CBIR; Predictive-Label Fuzzy Support Vector Machine for Small Sample Problem; Conclusion;
• Edition: 2nd ed
• Publisher Details: Boca Raton : Taylor & Francis
• Publication Date: 2010
• Copyright Date: 2010
• Extent: 1 online resource (xiv, 362 pages), illustrations
• Subjects: 621.36/7; Image processing -- Data processing; Image processing -- Digital techniques; Computational intelligence; Traitement d'images; Intelligence informatique; TECHNOLOGY & ENGINEERING -- Imaging Systems; Computational intelligence; Image processing -- Data processing; Image processing -- Digital techniques; Bildbehandling; Electronic books
• Languages: English
• ISBNs: 9781420084368; 1420084364; 1420084356; 9781420084351
• Related ISBNs: 9781420084351
• Notes: Note: Includes bibliographical references (pages 339-351) and index.; Note: Print version record.
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.