1st Edition
Multispectral Image Analysis Using the Object-Oriented Paradigm
By Kumar Navulur
Copyright 2007
204 Pages
42 Color & 117 B/W Illustrations
by
CRC Press
204 Pages
42 Color & 117 B/W Illustrations
by
CRC Press
204 Pages
by
CRC Press
Also available as eBook on:
Bringing a fresh new perspective to remote sensing, object-based image analysis is a paradigm shift from the traditional pixel-based approach. Featuring various practical examples to provide understanding of this new modus operandi, Multispectral Image Analysis Using the Object-Oriented Paradigm reviews the current image analysis methods and demonstrates advantages to improve information... Read more
Introduction
Background
Objects and Human Interpretation Process
Object-Oriented Paradigm
Organization of the Book
Multispectral Remote Sensing
Spatial Resolution
Spectral Resolution
Radiometric Resolution
Temporal Resolution
Multispectral Image Analysis
Why an Object-Oriented Approach?
Object Properties
Advantages of Object-Oriented Approach
Creating Objects
Image Segmentation Techniques
Creating and Classifying Objects at Multiple Scales
Object Classification
Creating Multiple Levels
Creating Class Hierarchy and Classifying Objects
Final Classification Using Object Relationships between Levels
Object-Based Image Analysis
Image Analysis Techniques
Supervised Classification Using Multispectral Information
Exploring the Spatial Dimension
Using Contextual Information
Taking Advantage of Morphology Parameters
Taking Advantage of Texture
Adding Temporal Dimension
Advanced Object Image Analysis
Techniques to Control Image Segmentation within eCognition
Techniques to Control Image Segmentation within eCognition
Multi-Scale Approach for Image Analysis
Objects vs. Spatial Resolution
Exploring the Parent-Child Object Relationships
Using Semantic Relationships
Taking Advantage of Ancillary Data
Accuracy Assessment
Sample Selection
Sampling Techniques
Ground Truth Collection
Accuracy Assessment Measures
References
Index
Background
Objects and Human Interpretation Process
Object-Oriented Paradigm
Organization of the Book
Multispectral Remote Sensing
Spatial Resolution
Spectral Resolution
Radiometric Resolution
Temporal Resolution
Multispectral Image Analysis
Why an Object-Oriented Approach?
Object Properties
Advantages of Object-Oriented Approach
Creating Objects
Image Segmentation Techniques
Creating and Classifying Objects at Multiple Scales
Object Classification
Creating Multiple Levels
Creating Class Hierarchy and Classifying Objects
Final Classification Using Object Relationships between Levels
Object-Based Image Analysis
Image Analysis Techniques
Supervised Classification Using Multispectral Information
Exploring the Spatial Dimension
Using Contextual Information
Taking Advantage of Morphology Parameters
Taking Advantage of Texture
Adding Temporal Dimension
Advanced Object Image Analysis
Techniques to Control Image Segmentation within eCognition
Techniques to Control Image Segmentation within eCognition
Multi-Scale Approach for Image Analysis
Objects vs. Spatial Resolution
Exploring the Parent-Child Object Relationships
Using Semantic Relationships
Taking Advantage of Ancillary Data
Accuracy Assessment
Sample Selection
Sampling Techniques
Ground Truth Collection
Accuracy Assessment Measures
References
Index
Biography
Kumar Navulur
". . . Navulur’s book makes a valuable contribution because it offers a well-organized reference to contemporary developments in object-oriented image analysis, along with various creative ideas for implementation of these methods in practical solutions."
– Matthew Ramspott, Department of Geography, Frostburg State University, in Photogrammetric Engineering & Remote Sensing, September 2007, Vol. 73, No. 9
