Image fusion /

Image fusion /

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Bibliographic Details
Author / Creator:Xiao, Gang, author.
Imprint:Singapore : Springer ; Shanghai, China : Shanghai Jiao Tong University Press, [2020]
Description:1 online resource (415 pages)
Language:English
Subject:
Optical data processing.
Multispectral imaging.
Computer vision.
Computer vision.
Multispectral imaging.
Optical data processing.
Electronic books.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/12607383
Hidden Bibliographic Details
Other authors / contributors:Bavirisetti, Durga Prasad, author.
Liu, Gang, author.
Zhang, Xingchen, author.
ISBN:9789811548673
9811548676
9811548668
9789811548666
Digital file characteristics:text file PDF
Notes:Includes bibliographical references.
Description based on online resource; title from digital title page (viewed on October 16, 2020).
Summary:This book systematically discusses the basic concepts, theories, research and latest trends in image fusion. It focuses on three image fusion categories - pixel, feature and decision - presenting various applications, such as medical imaging, remote sensing, night vision, robotics and autonomous vehicles. Further, it introduces readers to a new category: edge-preserving-based image fusion, and provides an overview of image fusion based on machine learning and deep learning. As such, it is a valuable resource for graduate students and scientists in the field of digital image processing and information fusion.
Other form:Print version: Xiao, Gang Image Fusion Singapore : Springer Singapore Pte. Limited,c2020 9789811548666
Standard no.:10.1007/978-981-15-4
Table of Contents:
  • Intro
  • Preface
  • Acknowledgments
  • Contents
  • About the Authors
  • Part I: Image Fusion Theories
  • Chapter 1: Introduction to Image Fusion
  • 1.1 History and Development
  • 1.1.1 History
  • 1.1.2 Development
  • 1.2 Image Fusion Fundamentals
  • 1.2.1 Necessity to Combine Information of Images
  • 1.2.2 Definition of Image Fusion
  • 1.2.3 Image Fusion Objective
  • 1.3 Categorization
  • 1.4 Fundamental Steps of an Image Fusion System
  • 1.5 Types of Image Fusion Systems
  • 1.6 Applications
  • 1.7 Summary and Outline of the Book
  • References
  • Chapter 2: Pixel-Level Image Fusion
  • 2.1 Introduction
  • 2.1.1 Single-Scale Image Fusion
  • 2.1.2 Multi-Scale Image Fusion
  • 2.1.2.1 Pyramid-Based Fusion
  • 2.1.2.2 Wavelet Transform-Based Fusion
  • 2.1.2.3 Filtering-Based Fusion
  • 2.2 Pyramid Image Fusion Method Based on Integrated Edge and Texture Information
  • 2.2.1 Background
  • 2.2.2 Fusion Framework
  • 2.2.3 Pyramid Image Fusion of Edge and Texture Information-Specific Steps
  • 2.2.4 Beneficial Effects
  • 2.3 Image Fusion Method Based on the Expected Maximum and Discrete Wavelet Frames
  • 2.3.1 Introduction
  • 2.3.2 Discrete Wavelet Frame Multi-Resolution Transform
  • 2.3.3 Basic Structure of the New Fusion Scheme
  • 2.3.4 Fusion of the Low-Frequency Band Using the EM Algorithm
  • 2.3.5 The Selection of the High-Frequency Band Using the Informative Importance Measure
  • 2.3.6 Computer Simulation
  • 2.3.7 Conclusions
  • 2.4 Image Fusion Method Based on Optimal Wavelet Filter Banks
  • 2.4.1 Introduction
  • 2.4.2 The Generic Multi-Resolution Image Fusion Algorithm
  • 2.4.3 Design Criteria of Filter Banks
  • 2.4.4 Optimization Design of Filter Bank for Image Fusion
  • 2.4.5 Experiments
  • 2.4.6 Conclusion
  • 2.5 Anisotropic Diffusion-Based Fusion of Infrared and Visible Sensor Images (ADF)
  • 2.5.1 Anisotropic Diffusion
  • 2.5.2 Anisotropic Diffusion-Based Fusion Method (ADF)
  • 2.5.2.1 Extracting Base and Detail Layers
  • 2.5.2.2 Detail Layer Fusion Based on KL Transform
  • 2.5.2.3 Base Layer Fusion
  • 2.5.2.4 Super Position of Final Detail and Base Layers
  • 2.5.3 Experimental Setup
  • 2.5.3.1 Image Database
  • 2.5.3.2 Fusion Metrics
  • 2.5.3.3 Methods for Comparison
  • 2.5.3.4 Effect of Free Parameters on the ADF Method
  • 2.5.4 Results and Analysis
  • 2.5.4.1 Qualitative Analysis
  • 2.5.4.2 Quantitative Analysis
  • 2.5.4.3 Computational Time
  • 2.6 Two-Scale Image Fusion of Infrared and Visible Images Using Saliency Detection
  • 2.6.1 Two-Scale Image Fusion (TIF)
  • 2.6.1.1 Two-Scale Image Decomposition
  • 2.6.1.2 Visual Saliency Detection
  • 2.6.1.3 Weight Map Construction
  • 2.6.1.4 Detail Layer Fusion
  • 2.6.1.5 Base Layer Fusion
  • 2.6.1.6 Two-Scale Image Reconstruction
  • 2.6.1.7 Color Image Fusion
  • 2.6.2 Experimental Setup
  • 2.6.2.1 Image Database
  • 2.6.2.2 Other Methods for Comparison
  • 2.6.2.3 Objective Fusion Metrics
  • 2.6.2.4 Parameter Analysis

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